Courses
Spring Term Schedule
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Spring 2019
Number  Title  Instructor  Time 

STT 201 (MTH 201)
KRISHNAN A
MW 2:00PM  3:15PM


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 08:0009:30am Common Exam time. BUILDING: GRGEN  ROOM: 108 PREREQUISITES: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201. 

STT 201 (MTH 201)
TUCKER T
MW 10:25AM  11:40AM


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 08:0009:30am Common Exam time. BUILDING: B&L  ROOM: 106 PREREQUISITES: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201. 

STT 203 (STT 203)
BAUTISTA J
TR 9:40AM  10:55AM


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. BUILDING: HARK  ROOM: 115 PREREQUISITES: STT 201 or familiarity with the elementary principles of probability, expected value, variance and covariance. 

STT 203 (STT 203)
PODURI R
TR 11:05AM  12:20PM


No description BUILDING: HYLAN  ROOM: 202 PREREQUISITES: STT 201 or familiarity with the elementary principles of probability, expected value, variance and covariance. 

STT 211
ZAINO N
MW 11:50AM  1:05PM


This course is a noncalculus based introduction to the tools for collecting, analyzing, and drawing conclusions from data, focusing on conceptual understanding and basic analyses. Students are exposed to four themes: 1.Understanding data and turning data into usable information through graphs and numerical methods 2. Collecting data through experiments and observational studies. 3. Exploring random phenomena using probability as the basis for statistical inference 4. Estimating parameters and performing statistical inference. Advanced topics include regression, ANOVA, and contingency tables. Applications are taken from the social sciences and humanities. Calculations are performed using TI83/TI84 calculators. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students looking for a terminal statistics course that provides a foundation in statistical understanding. BUILDING: HYLAN  ROOM: 202 

STT 212
MCDERMOTT M
TR 11:05AM  12:20PM


This course is a noncalculus 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 upperlevel methodology courses BUILDING: STRNG  ROOM: LOWER 

STT 212
GRZESIK K
MW 2:00PM  3:15PM


This course is a noncalculus 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 upperlevel methodology courses BUILDING: LATT  ROOM: 201 

STT 212
CIMINELLI J
TR 12:30PM  1:45PM


This course is a noncalculus 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 upperlevel methodology courses BUILDING: MEL  ROOM: 203 

STT 213
MCDERMOTT M
TR 2:00PM  3:15PM


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 upperlevel methodology courses. BUILDING: CSB  ROOM: 209 PREREQUISITES: MTH 141 or equivalent. 

STT 214 (BIO 214)
PRESGRAVES D
TR 12:30PM  1:45PM


This course will familiarize students with statistical concepts necessary to evaluate the primary literature in the biological sciences. It will improve studentsâ€™ statistical literacy and sharpen analytical thinking. Topics covered in the course will include: descriptive statistics and graphics, estimation, elementary probability theory, statistical distributions, hypothesis testing, goodness of fit, experimental design, correlation, analysis of variance and regression. If students would like to learn R, students should consider the lab, BIO 218P. The lab is not required for BIO 214. Students will not receive credit for BIO/STT 214 if they have already completed STT 211, 212, 213 or received equivalency for AP credit. BUILDING: GRGEN  ROOM: 109 

STT 214 (BIO 214)
PRESGRAVES D
T 4:15PM  5:05PM


No description BUILDING: GEN  ROOM: 321 

STT 214 (BIO 214)
PRESGRAVES D
M 5:15PM  6:05PM


No description BUILDING: GEN  ROOM: 321 

STT 214 (BIO 214)
PRESGRAVES D
W 5:00PM  5:50PM


No description BUILDING: GEN  ROOM: 323 

STT 214 (BIO 214)
PRESGRAVES D
F 5:15PM  6:05PM


No description BUILDING: GEN  ROOM: 321 

STT 214W
–
–


Optional UpperLevel Writing Course for BIO 214 BUILDING:  ROOM: 

STT 216 (STT 216)
ZAINO N
TR 9:40AM  10:55AM


This course focuses on the practical use of statistical methods beyond what is covered in STT 211, STT 212 and STT 213. The level of sophistication is high when it comes to the models and methods needed to analyze data and interpret results. Topics include randomization tests, bootstrapping, nonparametric tests, ANOVA models (fixed, random and mixed models, crossed and nested), multiple comparisons and linear contrasts, multiple linear regression, binary logistic regression and related topics. The course uses examples and case studies from both the natural and social sciences. The use of computer programs is emphasized for calculations and there is a strong emphasis on assumptions, models and interpretation of results. BUILDING: CSB  ROOM: 209 PREREQUISITES: STT 211, STT 212, or STT 213 

STT 223
CIMINELLI J
TR 11:05AM  12:20PM


In this course, the Bayesian approach to statistical inference will be explored. Topics to be discussed include single and multiple parameter models under conjugacy, uninformative and informative prior distribution specifications, hierarchical models, model checking, and modern computational techniques for posterior distribution approximation (e.g. Markov chain Monte Carlo). Basic familiarity with the R computing environment is assumed, as the course includes extensive R programming. Applications will be drawn from across the social and natural sciences, providing a strong foundation for applied data analyses within the Bayesian statistical framework. BUILDING: HYLAN  ROOM: 102 PREREQUISITES: STT 203 and MTH 164, or instructor permission 

STT 226W
PODURI R
TR 2:00PM  3:15PM


Simple linear, multiple, and polynomial regression methods and applications; ordinary and generalized least squares, estimation, tests of hypotheses, and confidence intervals, and simultaneous inference, and computer packages. Computer programs including JMP and SAS. BUILDING: HYLAN  ROOM: 101 PREREQUISITES: STT 211, STT 212 or 213, and STT 203 or equivalent.. 

STT 276
GRZESIK K
MW 10:25AM  11:40AM


This course offers an introduction to statistical computing in the R environment. To start, focus is placed on assigning objects, creating data structures, applying Boolean logic, importing and subsetting data, data manipulation (both long and short formats), and implementing elementary commands and builtin functions from R packages. In the second portion of the course, students learn more advanced topics of writing loops, developing functions, building graphics, debugging code, and text mining. Topics will be illustrated using key statistical tools, including basic data summarization and exploration, linear models, and simulations. The course will rely upon the use of R Markdown as an essential tool for effectively integrating R code and output into presentable reports. Basic skills with a text editor (such as Notepad) and Microsoft Excel are assumed, as is basic knowledge of statistical inference. BUILDING: GAVET  ROOM: 244 PREREQUISITES: STT 211, 212, 213, or equivalent 

STT 390
–
–


No description BUILDING:  ROOM: 

STT 391
–
–


No description BUILDING:  ROOM: 

STT 391W
–
–


No description BUILDING:  ROOM: 

STT 394
–
–


No description BUILDING:  ROOM: 

STT 591
–
–


No description BUILDING:  ROOM: 

STT 999
–
–


No description BUILDING:  ROOM: 
Spring 2019
Number  Title  Instructor  Time 

Monday  
STT 214 (BIO 214)
PRESGRAVES D
M 5:15PM  6:05PM


No description BUILDING: GEN  ROOM: 321 

Monday and Wednesday  
STT 201 (MTH 201)
TUCKER T
MW 10:25AM  11:40AM


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 08:0009:30am Common Exam time. BUILDING: B&L  ROOM: 106 PREREQUISITES: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201. 

STT 276
GRZESIK K
MW 10:25AM  11:40AM


This course offers an introduction to statistical computing in the R environment. To start, focus is placed on assigning objects, creating data structures, applying Boolean logic, importing and subsetting data, data manipulation (both long and short formats), and implementing elementary commands and builtin functions from R packages. In the second portion of the course, students learn more advanced topics of writing loops, developing functions, building graphics, debugging code, and text mining. Topics will be illustrated using key statistical tools, including basic data summarization and exploration, linear models, and simulations. The course will rely upon the use of R Markdown as an essential tool for effectively integrating R code and output into presentable reports. Basic skills with a text editor (such as Notepad) and Microsoft Excel are assumed, as is basic knowledge of statistical inference. BUILDING: GAVET  ROOM: 244 PREREQUISITES: STT 211, 212, 213, or equivalent 

STT 211
ZAINO N
MW 11:50AM  1:05PM


This course is a noncalculus based introduction to the tools for collecting, analyzing, and drawing conclusions from data, focusing on conceptual understanding and basic analyses. Students are exposed to four themes: 1.Understanding data and turning data into usable information through graphs and numerical methods 2. Collecting data through experiments and observational studies. 3. Exploring random phenomena using probability as the basis for statistical inference 4. Estimating parameters and performing statistical inference. Advanced topics include regression, ANOVA, and contingency tables. Applications are taken from the social sciences and humanities. Calculations are performed using TI83/TI84 calculators. Students may earn degree credit for only one of these courses: STT211, STT212, STT213, and BIO/STT214. This course is recommended for students looking for a terminal statistics course that provides a foundation in statistical understanding. BUILDING: HYLAN  ROOM: 202 

STT 201 (MTH 201)
KRISHNAN A
MW 2:00PM  3:15PM


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 08:0009:30am Common Exam time. BUILDING: GRGEN  ROOM: 108 PREREQUISITES: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201. 

STT 212
GRZESIK K
MW 2:00PM  3:15PM


This course is a noncalculus 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 upperlevel methodology courses BUILDING: LATT  ROOM: 201 

Tuesday  
STT 214 (BIO 214)
PRESGRAVES D
T 4:15PM  5:05PM


No description BUILDING: GEN  ROOM: 321 

Tuesday and Thursday  
STT 216 (STT 216)
ZAINO N
TR 9:40AM  10:55AM


This course focuses on the practical use of statistical methods beyond what is covered in STT 211, STT 212 and STT 213. The level of sophistication is high when it comes to the models and methods needed to analyze data and interpret results. Topics include randomization tests, bootstrapping, nonparametric tests, ANOVA models (fixed, random and mixed models, crossed and nested), multiple comparisons and linear contrasts, multiple linear regression, binary logistic regression and related topics. The course uses examples and case studies from both the natural and social sciences. The use of computer programs is emphasized for calculations and there is a strong emphasis on assumptions, models and interpretation of results. BUILDING: CSB  ROOM: 209 PREREQUISITES: STT 211, STT 212, or STT 213 

STT 203 (STT 203)
BAUTISTA J
TR 9:40AM  10:55AM


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. BUILDING: HARK  ROOM: 115 PREREQUISITES: STT 201 or familiarity with the elementary principles of probability, expected value, variance and covariance. 

STT 203 (STT 203)
PODURI R
TR 11:05AM  12:20PM


No description BUILDING: HYLAN  ROOM: 202 PREREQUISITES: STT 201 or familiarity with the elementary principles of probability, expected value, variance and covariance. 

STT 212
MCDERMOTT M
TR 11:05AM  12:20PM


This course is a noncalculus 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 upperlevel methodology courses BUILDING: STRNG  ROOM: LOWER 

STT 223
CIMINELLI J
TR 11:05AM  12:20PM


In this course, the Bayesian approach to statistical inference will be explored. Topics to be discussed include single and multiple parameter models under conjugacy, uninformative and informative prior distribution specifications, hierarchical models, model checking, and modern computational techniques for posterior distribution approximation (e.g. Markov chain Monte Carlo). Basic familiarity with the R computing environment is assumed, as the course includes extensive R programming. Applications will be drawn from across the social and natural sciences, providing a strong foundation for applied data analyses within the Bayesian statistical framework. BUILDING: HYLAN  ROOM: 102 PREREQUISITES: STT 203 and MTH 164, or instructor permission 

STT 212
CIMINELLI J
TR 12:30PM  1:45PM


This course is a noncalculus 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 upperlevel methodology courses BUILDING: MEL  ROOM: 203 

STT 214 (BIO 214)
PRESGRAVES D
TR 12:30PM  1:45PM


This course will familiarize students with statistical concepts necessary to evaluate the primary literature in the biological sciences. It will improve studentsâ€™ statistical literacy and sharpen analytical thinking. Topics covered in the course will include: descriptive statistics and graphics, estimation, elementary probability theory, statistical distributions, hypothesis testing, goodness of fit, experimental design, correlation, analysis of variance and regression. If students would like to learn R, students should consider the lab, BIO 218P. The lab is not required for BIO 214. Students will not receive credit for BIO/STT 214 if they have already completed STT 211, 212, 213 or received equivalency for AP credit. BUILDING: GRGEN  ROOM: 109 

STT 213
MCDERMOTT M
TR 2:00PM  3:15PM


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 upperlevel methodology courses. BUILDING: CSB  ROOM: 209 PREREQUISITES: MTH 141 or equivalent. 

STT 226W
PODURI R
TR 2:00PM  3:15PM


Simple linear, multiple, and polynomial regression methods and applications; ordinary and generalized least squares, estimation, tests of hypotheses, and confidence intervals, and simultaneous inference, and computer packages. Computer programs including JMP and SAS. BUILDING: HYLAN  ROOM: 101 PREREQUISITES: STT 211, STT 212 or 213, and STT 203 or equivalent.. 

Wednesday  
STT 214 (BIO 214)
PRESGRAVES D
W 5:00PM  5:50PM


No description BUILDING: GEN  ROOM: 323 

Friday  
STT 214 (BIO 214)
PRESGRAVES D
F 5:15PM  6:05PM


No description BUILDING: GEN  ROOM: 321 

TBA  
STT 214W
–
–


Optional UpperLevel Writing Course for BIO 214 BUILDING:  ROOM: 

STT 390
–
–


No description BUILDING:  ROOM: 

STT 391
–
–


No description BUILDING:  ROOM: 

STT 391W
–
–


No description BUILDING:  ROOM: 

STT 394
–
–


No description BUILDING:  ROOM: 

STT 591
–
–


No description BUILDING:  ROOM: 

STT 999
–
–


No description BUILDING:  ROOM: 