Fall Term Schedule
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Fall 2023
| Number | Title | Instructor | Time |
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STAT 201-1
Arda Huseyin Demirhan
MW 10:25AM - 11:40AM
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Cross Listed: MTH 201 (P), STT 201 Prerequisites: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201. Description: Probability spaces; combinatorial problems; random variables and expectations; discrete and continuous distributions; generating functions; independence and dependence; binomial, normal, and Poisson laws; laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time.
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STAT 201-14
Kalyani Madhu
T 3:25PM - 4:40PM
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Probability spaces, combinatorial problems, random variables and expectations, discrete and continuous distributions, generating functions, independence and dependence, binomial, normal, and Poisson laws, laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently. Same as MTH 201.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time.
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STAT 201-2
Mary Cook
MW 2:00PM - 3:15PM
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Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent, MATH 164 recommended. Same as STAT 201. Description: Probability spaces; combinatorial problems; random variables and expectations; discrete and continuous distributions; generating functions; independence and dependence; binomial, normal, and Poisson laws; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time.
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STAT 201-3
Joshua Sumpter
TR 9:40AM - 10:55AM
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Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent, MATH 164 recommended. Same as STAT 201. Probability spaces, combinatorial problems, random variables and expectations, discrete and continuous distributions, generating functions, independence and dependence, binomial, normal, and Poisson laws, laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently. Same as MTH 201.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time.
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STAT 201-6
Kalyani Madhu
F 3:25PM - 4:40PM
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Probability spaces, combinatorial problems, random variables and expectations, discrete and continuous distributions, generating functions, independence and dependence, binomial, normal, and Poisson laws, laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently. Same as MTH 201.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time.
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STAT 203-1
Javier Bautista
TR 3:25PM - 4:40PM
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Cross Listed: MTH 203 (P), STT 203 Prerequisites: MTH 201 Description: Discrete and continuous probability distributions and their properties. Principle of statistical estimation and inference. Point and interval estimation. Maximum likelihood method for estimation and inference. Tests of hypotheses and confidence intervals, contingency tables, and related topics.
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STAT 212-1
Katherine Grzesik
MW 12:30PM - 1:45PM
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Class Info: YOU MUST REGISTER FOR A WORKSHOP WHEN REGISTERING FOR THE MAIN COURSE. Description: This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses.
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STAT 212-10
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W 7:40PM - 8:55PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-11
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R 12:30PM - 1:45PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-12
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R 2:00PM - 3:15PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-13
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R 7:40PM - 8:55PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-14
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F 12:30PM - 1:45PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-15
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F 3:25PM - 4:40PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-16
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F 4:50PM - 6:05PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-17
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R 6:15PM - 7:30PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-2
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TR 11:05AM - 12:20PM
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Class Info: YOU MUST REGISTER FOR A WORKSHOP WHEN REGISTERING FOR THE MAIN COURSE. Description: This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses.
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STAT 212-3
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R 3:25PM - 4:40PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-4
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R 6:15PM - 7:30PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-5
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F 10:25AM - 11:40AM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-6
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W 6:15PM - 7:30PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-7
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F 2:00PM - 3:15PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-8
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R 7:40PM - 8:55PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 212-9
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W 4:50PM - 6:05PM
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses
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STAT 213-1
Aruni Jayathilaka
MW 11:50AM - 1:05PM
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Class Info: YOU MUST REGISTER FOR A WORKSHOP WHEN REGISTERING FOR THE MAIN COURSE. Prerequisites: MATH 141 or equivalent. Description: This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STAT 211, STAT 212, STAT 213, or BIOL/STAT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-10
Aruni Jayathilaka
T 6:15PM - 7:30PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-11
Aruni Jayathilaka
T 3:25PM - 4:40PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-12
Aruni Jayathilaka
W 10:25AM - 11:40AM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-13
Aruni Jayathilaka
W 4:50PM - 6:05PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-14
Aruni Jayathilaka
W 6:15PM - 7:30PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-2
Aruni Jayathilaka
M 2:00PM - 3:15PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-3
Aruni Jayathilaka
W 2:00PM - 3:15PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-4
Aruni Jayathilaka
W 3:25PM - 4:40PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-5
Aruni Jayathilaka
M 4:50PM - 6:05PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-6
Aruni Jayathilaka
M 6:15PM - 7:30PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-8
Aruni Jayathilaka
T 12:30PM - 1:45PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 213-9
Aruni Jayathilaka
T 4:50PM - 6:05PM
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This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses.
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STAT 216-1
Nicholas Zaino
TR 9:40AM - 10:55AM
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Prerequisites: STAT 211, STAT 212, or STAT 213. Co-located with STAT 416 Description: STAT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable reports.
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STAT 216-2
Aruni Jayathilaka
MW 2:00PM - 3:15PM
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Prerequisites: STAT 211, STAT 212, or STAT 213 Description: STAT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable reports.
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STAT 216-3
Joseph Ciminelli
TR 12:30PM - 1:45PM
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Prerequisites: STT 211, STT 212, or STT 213. Description: THIS SECTION ONLY OPEN TO FIRST YEAR STUDENTS AND SOPHOMORES. STT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable report
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STAT 218-1
Joseph Ciminelli
TR 11:05AM - 12:20PM
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Co-located with STT 418, STT 218 This course offers an introduction to methods used for analyzing categorical data. The first portion of this course focuses on contingency table analyses. In particular, both two-way and three-way tables are introduced, along with inferential methods for determining significant associations between categorical responses. In the second portion of the course, emphasis is placed on regression models for categorical outcomes that are binary, polytomous, ordinal, or counts. Particular attention is given to logistic, probit, and log-linear models, along with associated inferential tests and model diagnostics. Examples and applications are taken from public health, epidemiology, and the behavioral and social sciences. R is introduced as the primary statistical software for performing data analyses.
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STAT 219-2
Katherine Grzesik
MW 10:25AM - 11:40AM
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Co-located with STT 419, STT 219 Prerequisites: STT 216, and MTH 142. STT 203 is recommended Description: This course offers an applied introduction to nonparametric statistical methods and modeling techniques. The first half of the course covers nonparametric hypothesis testing and inference. The second half covers density estimation techniques, smoothing splines, local polynomial regression, and cross-validation. The course culminates in an applied project involving nonparametric techniques to analyze real-world data. R/RStudio will be used for computation, so previous experience with such software is recommended.
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STAT 221W-1
Nicholas Zaino
TR 12:30PM - 1:45PM
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Cross Listed: BST 421, STT 221W (P) Prerequisites: STT 211, STT 212 or STT 213, and 203 or equivalent. Description: Simple random, stratified, systematic, and cluster sampling; estimation of the means, proportions, variance, and ratios of a finite population. Ratio and regression methods of estimation and the use of auxiliary information. The nonresponse problem. Prerequisite: familiarity with the concepts of expectation, variance, covariance and correlation.
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STAT 262-1
Aruni Jayathilaka
TR 2:00PM - 3:15PM
|
|
This course will cover foundational concepts in descriptive analyses, probability, and statistical inference. Topics to be covered include data exploration through descriptive statistics (with a heavy emphasis on using R for such analyses), elementary probability, diagnostic testing, combinatorics, random variables, elementary distribution theory, statistical inference, and statistical modeling. The inference portion of the course will focus on building and applying hypothesis tests and confidence intervals for population means, proportions, variances, and correlations. Non-parametric alternatives will also be introduced. The modeling portion of the course will include ANOVA, and simple and multiple regression and their respective computational methods. Students will be introduced to the R statistical computing environment. PREREQUISITES: MTH 150 or MTH 150A; AND MTH 142 or MTH 161 or MTH 171
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STAT 277-1
Javier Bautista
TR 9:40AM - 10:55AM
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Cross Listed: STT 277 (P), STT 477 Prerequisites: STT 211, STT 212 or STT 213 and STT 216 or STT 226W. CROSS LISTED with STT 477. Description: The first half of this course covers programming in R, SAS, and JMP. The second half explores the use of this software to understand data from observational studies. The student will learn the philosophy, capabilities, and pitfalls of exploratory data analysis. Univariate, bivariate and multivariate methods will be introduced. Graphical methods will be emphasized, but numerically-oriented procedures such as linear models will be included where appropriate. Each student will analyze a real-life data set in some depth and write a report. Registration priority will be given to Statistics majors who will be taking the course in their senior year. Basic skills with the Windows operating system, a text editor (such as Notepad), and Microsoft Excel is assumed.
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STAT 390-1
–
–
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No description |
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STAT 390A-1
Katherine Grzesik
–
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No description |
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STAT 390A-2
Katherine Grzesik
–
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No description |
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STAT 390A-3
Maria McDermott
–
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No description |
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STAT 392-1
–
–
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STAT 392 - an online independent study form is available at: https://www.rochester.edu/college/ccas/handbook/independent-studies.html |
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STAT 394-1
–
–
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Registration for Independent Study courses needs to be completed thru the https://secure1.rochester.edu/registrar/forms/independent-study-form.php instructions for online independent study registration |
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STAT 416-1
Nicholas Zaino
TR 9:40AM - 10:55AM
|
|
Co-located with STAT 216-1 STAT 416-1 Prerequisites: STAT 211, STAT 212, or STAT 213. Description: STAT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable reports.
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STAT 418-1
Joseph Ciminelli
TR 11:05AM - 12:20PM
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|
Co-located with STT 418, STT 218 This course offers an introduction to methods used for analyzing categorical data. The first portion of this course focuses on contingency table analyses. In particular, both two-way and three-way tables are introduced, along with inferential methods for determining significant associations between categorical responses. In the second portion of the course, emphasis is placed on regression models for categorical outcomes that are binary, polytomous, ordinal, or counts. Particular attention is given to logistic, probit, and log-linear models, along with associated inferential tests and model diagnostics. Examples and applications are taken from public health, epidemiology, and the behavioral and social sciences. R is introduced as the primary statistical software for performing data analyses.
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STAT 419-2
Katherine Grzesik
MW 10:25AM - 11:40AM
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Co-located with STT 419, STT 219 Prerequisites: STT 216, and MTH 142. STT 203 is recommended Description: This course offers an applied introduction to nonparametric statistical methods and modeling techniques. The first half of the course covers nonparametric hypothesis testing and inference. The second half covers density estimation techniques, smoothing splines, local polynomial regression, and cross-validation. The course culminates in an applied project involving nonparametric techniques to analyze real-world data. R/RStudio will be used for computation, so previous experience with such software is recommended.
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STAT 477-1
Javier Bautista
TR 9:40AM - 10:55AM
|
|
Cross Listed: STT 277 (P), STT 477 Prerequisites: STT 211, STT 212 or STT 213 and STT 216 or STT 226W. CROSS LISTED with STT 477. Description: The first half of this course covers programming in R, SAS, and JMP. The second half explores the use of this software to understand data from observational studies. The student will learn the philosophy, capabilities, and pitfalls of exploratory data analysis. Univariate, bivariate and multivariate methods will be introduced. Graphical methods will be emphasized, but numerically-oriented procedures such as linear models will be included where appropriate. Each student will analyze a real-life data set in some depth and write a report. Registration priority will be given to Statistics majors who will be taking the course in their senior year. Basic skills with the Windows operating system, a text editor (such as Notepad), and Microsoft Excel is assumed.
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Fall 2023
| Number | Title | Instructor | Time |
|---|---|
| Monday | |
|
STAT 213-2
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 213-5
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 213-6
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
| Monday and Wednesday | |
|
STAT 201-1
Arda Huseyin Demirhan
|
|
|
Cross Listed: MTH 201 (P), STT 201 Prerequisites: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201. Description: Probability spaces; combinatorial problems; random variables and expectations; discrete and continuous distributions; generating functions; independence and dependence; binomial, normal, and Poisson laws; laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time. |
|
|
STAT 219-2
Katherine Grzesik
|
|
|
Co-located with STT 419, STT 219 Prerequisites: STT 216, and MTH 142. STT 203 is recommended Description: This course offers an applied introduction to nonparametric statistical methods and modeling techniques. The first half of the course covers nonparametric hypothesis testing and inference. The second half covers density estimation techniques, smoothing splines, local polynomial regression, and cross-validation. The course culminates in an applied project involving nonparametric techniques to analyze real-world data. R/RStudio will be used for computation, so previous experience with such software is recommended. |
|
|
STAT 419-2
Katherine Grzesik
|
|
|
Co-located with STT 419, STT 219 Prerequisites: STT 216, and MTH 142. STT 203 is recommended Description: This course offers an applied introduction to nonparametric statistical methods and modeling techniques. The first half of the course covers nonparametric hypothesis testing and inference. The second half covers density estimation techniques, smoothing splines, local polynomial regression, and cross-validation. The course culminates in an applied project involving nonparametric techniques to analyze real-world data. R/RStudio will be used for computation, so previous experience with such software is recommended. |
|
|
STAT 213-1
Aruni Jayathilaka
|
|
|
Class Info: YOU MUST REGISTER FOR A WORKSHOP WHEN REGISTERING FOR THE MAIN COURSE. Prerequisites: MATH 141 or equivalent. Description: This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STAT 211, STAT 212, STAT 213, or BIOL/STAT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 212-1
Katherine Grzesik
|
|
|
Class Info: YOU MUST REGISTER FOR A WORKSHOP WHEN REGISTERING FOR THE MAIN COURSE. Description: This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses. |
|
|
STAT 201-2
Mary Cook
|
|
|
Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent, MATH 164 recommended. Same as STAT 201. Description: Probability spaces; combinatorial problems; random variables and expectations; discrete and continuous distributions; generating functions; independence and dependence; binomial, normal, and Poisson laws; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time. |
|
|
STAT 216-2
Aruni Jayathilaka
|
|
|
Prerequisites: STAT 211, STAT 212, or STAT 213 Description: STAT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable reports. |
|
| Tuesday | |
|
STAT 213-8
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 201-14
Kalyani Madhu
|
|
|
Probability spaces, combinatorial problems, random variables and expectations, discrete and continuous distributions, generating functions, independence and dependence, binomial, normal, and Poisson laws, laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently. Same as MTH 201.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time. |
|
|
STAT 213-11
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 213-9
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 213-10
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
| Tuesday and Thursday | |
|
STAT 201-3
Joshua Sumpter
|
|
|
Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent, MATH 164 recommended. Same as STAT 201. Probability spaces, combinatorial problems, random variables and expectations, discrete and continuous distributions, generating functions, independence and dependence, binomial, normal, and Poisson laws, laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently. Same as MTH 201.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time. |
|
|
STAT 216-1
Nicholas Zaino
|
|
|
Prerequisites: STAT 211, STAT 212, or STAT 213. Co-located with STAT 416 Description: STAT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable reports. |
|
|
STAT 277-1
Javier Bautista
|
|
|
Cross Listed: STT 277 (P), STT 477 Prerequisites: STT 211, STT 212 or STT 213 and STT 216 or STT 226W. CROSS LISTED with STT 477. Description: The first half of this course covers programming in R, SAS, and JMP. The second half explores the use of this software to understand data from observational studies. The student will learn the philosophy, capabilities, and pitfalls of exploratory data analysis. Univariate, bivariate and multivariate methods will be introduced. Graphical methods will be emphasized, but numerically-oriented procedures such as linear models will be included where appropriate. Each student will analyze a real-life data set in some depth and write a report. Registration priority will be given to Statistics majors who will be taking the course in their senior year. Basic skills with the Windows operating system, a text editor (such as Notepad), and Microsoft Excel is assumed. |
|
|
STAT 416-1
Nicholas Zaino
|
|
|
Co-located with STAT 216-1 STAT 416-1 Prerequisites: STAT 211, STAT 212, or STAT 213. Description: STAT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable reports. |
|
|
STAT 477-1
Javier Bautista
|
|
|
Cross Listed: STT 277 (P), STT 477 Prerequisites: STT 211, STT 212 or STT 213 and STT 216 or STT 226W. CROSS LISTED with STT 477. Description: The first half of this course covers programming in R, SAS, and JMP. The second half explores the use of this software to understand data from observational studies. The student will learn the philosophy, capabilities, and pitfalls of exploratory data analysis. Univariate, bivariate and multivariate methods will be introduced. Graphical methods will be emphasized, but numerically-oriented procedures such as linear models will be included where appropriate. Each student will analyze a real-life data set in some depth and write a report. Registration priority will be given to Statistics majors who will be taking the course in their senior year. Basic skills with the Windows operating system, a text editor (such as Notepad), and Microsoft Excel is assumed. |
|
|
STAT 212-2
–
|
|
|
Class Info: YOU MUST REGISTER FOR A WORKSHOP WHEN REGISTERING FOR THE MAIN COURSE. Description: This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses. |
|
|
STAT 218-1
Joseph Ciminelli
|
|
|
Co-located with STT 418, STT 218 This course offers an introduction to methods used for analyzing categorical data. The first portion of this course focuses on contingency table analyses. In particular, both two-way and three-way tables are introduced, along with inferential methods for determining significant associations between categorical responses. In the second portion of the course, emphasis is placed on regression models for categorical outcomes that are binary, polytomous, ordinal, or counts. Particular attention is given to logistic, probit, and log-linear models, along with associated inferential tests and model diagnostics. Examples and applications are taken from public health, epidemiology, and the behavioral and social sciences. R is introduced as the primary statistical software for performing data analyses. |
|
|
STAT 418-1
Joseph Ciminelli
|
|
|
Co-located with STT 418, STT 218 This course offers an introduction to methods used for analyzing categorical data. The first portion of this course focuses on contingency table analyses. In particular, both two-way and three-way tables are introduced, along with inferential methods for determining significant associations between categorical responses. In the second portion of the course, emphasis is placed on regression models for categorical outcomes that are binary, polytomous, ordinal, or counts. Particular attention is given to logistic, probit, and log-linear models, along with associated inferential tests and model diagnostics. Examples and applications are taken from public health, epidemiology, and the behavioral and social sciences. R is introduced as the primary statistical software for performing data analyses. |
|
|
STAT 216-3
Joseph Ciminelli
|
|
|
Prerequisites: STT 211, STT 212, or STT 213. Description: THIS SECTION ONLY OPEN TO FIRST YEAR STUDENTS AND SOPHOMORES. STT 216 offers a second course in foundational techniques of statistical analyses, focusing on advanced inference topics (power, inference for variances and correlations, nonparametric testing, exact binomial tests, violations of assumptions), regression modeling (OLS regression, multiple regression, model diagnostics, outlier analysis, transformations, variable selection, logistic models), and analysis of variance (1- and 2-way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is non-calculus based and will focus on the practical use of statistical techniques for data analyses rather than on theory. As such, this course will rely upon the use of statistical software as a tool for examining data and compiling results into presentable report |
|
|
STAT 221W-1
Nicholas Zaino
|
|
|
Cross Listed: BST 421, STT 221W (P) Prerequisites: STT 211, STT 212 or STT 213, and 203 or equivalent. Description: Simple random, stratified, systematic, and cluster sampling; estimation of the means, proportions, variance, and ratios of a finite population. Ratio and regression methods of estimation and the use of auxiliary information. The nonresponse problem. Prerequisite: familiarity with the concepts of expectation, variance, covariance and correlation. |
|
|
STAT 262-1
Aruni Jayathilaka
|
|
|
This course will cover foundational concepts in descriptive analyses, probability, and statistical inference. Topics to be covered include data exploration through descriptive statistics (with a heavy emphasis on using R for such analyses), elementary probability, diagnostic testing, combinatorics, random variables, elementary distribution theory, statistical inference, and statistical modeling. The inference portion of the course will focus on building and applying hypothesis tests and confidence intervals for population means, proportions, variances, and correlations. Non-parametric alternatives will also be introduced. The modeling portion of the course will include ANOVA, and simple and multiple regression and their respective computational methods. Students will be introduced to the R statistical computing environment. PREREQUISITES: MTH 150 or MTH 150A; AND MTH 142 or MTH 161 or MTH 171 |
|
|
STAT 203-1
Javier Bautista
|
|
|
Cross Listed: MTH 203 (P), STT 203 Prerequisites: MTH 201 Description: Discrete and continuous probability distributions and their properties. Principle of statistical estimation and inference. Point and interval estimation. Maximum likelihood method for estimation and inference. Tests of hypotheses and confidence intervals, contingency tables, and related topics. |
|
| Wednesday | |
|
STAT 213-12
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 213-3
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 213-4
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 212-9
–
|
|
|
This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
|
|
STAT 213-13
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
|
|
STAT 212-6
–
|
|
|
This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
|
|
STAT 213-14
Aruni Jayathilaka
|
|
|
This course is an introduction to statistical methodology, focusing on the probability and statistical theory underlying the estimation of parameters and testing of hypotheses. Students are exposed to basic data exploration, summarization of graphical display of data, axioms of probability, distributions and related theory, parameter estimation, and statistical inference. Advanced topics include linear correlation and regression analysis. Students will perform calculations with statistical software such as R/RStudio. Please note that, because of the significant overlap between them, students may earn credit for only one of these courses: STT 211, STT 212, STT 213, or BIO/STT 214.This course is recommend for students majoring in Statistics, Economics, or Computer Science, or students looking for a mathematical introduction to statistics who are likely to continue on to other upper-level methodology courses. |
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STAT 212-10
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-11
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-12
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-3
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-17
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-4
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-13
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-8
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-5
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-14
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-7
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 201-6
Kalyani Madhu
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Probability spaces, combinatorial problems, random variables and expectations, discrete and continuous distributions, generating functions, independence and dependence, binomial, normal, and Poisson laws, laws of large numbers. MTH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MTH 162 and 201 cannot be taken concurrently. Same as MTH 201.This course uses the Tuesday/Thursday 08:00-09:30am Common Exam time. |
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STAT 212-15
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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STAT 212-16
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This course is a non-calculus based introduction to statistical methodology and analyses that focuses on providing students with the tools and computational experience needed to analyze data in the applied setting. Topics to be covered include data collection through experiments and observational studies, numerical and graphical data summarization, basic probability rules, statistical distributions, parameter estimation, and methods of statistical inference, regression analysis, ANOVA, and contingency tables. Applications are taken from the social and natural sciences. Calculations are performed with statistical software such as R/RStudio. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students majoring/minoring in statistics and students in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upper-level methodology courses |
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