Fall Term Schedule
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Fall 2024
Number  Title  Instructor  Time 

STAT 18002
Katherine Grzesik
MW 2:00PM  3:15PM


This course is a noncalculus based introduction to statistical analyses that focuses on 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. Calculations are performed with statistical software such as R/RStudio. This course is recommended for students majoring/minoring in statistics, fulfilling premedical requirement, or in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upperlevel methodology courses. Students may earn degree credit for only one of these courses: STAT 180, STAT 190, STAT 212, STAT 213, ECON 230, PSCI 200.


STAT 18010
Katherine Grzesik
W 7:40PM  8:55PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18011
Katherine Grzesik
R 12:30PM  1:45PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18012
Katherine Grzesik
R 2:00PM  3:15PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18013
Katherine Grzesik
R 7:40PM  8:55PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18014
Katherine Grzesik
F 12:30PM  1:45PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18015
Katherine Grzesik
F 3:25PM  4:40PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18016
Katherine Grzesik
F 4:50PM  6:05PM


T This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. I 200.


STAT 18017
Katherine Grzesik
R 6:15PM  7:30PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18018
Katherine Grzesik
F 2:00PM  3:15PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18019
Katherine Grzesik
R 3:25PM  4:40PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18020
Katherine Grzesik
R 6:15PM  7:30PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18021
Katherine Grzesik
F 10:25AM  11:40AM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18022
Katherine Grzesik
W 6:15PM  7:30PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18023
Katherine Grzesik
F 2:00PM  3:15PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18024
Katherine Grzesik
R 7:40PM  8:55PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18025
Katherine Grzesik
W 4:50PM  6:05PM


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 18101
Joseph Ciminelli
7:00PM  7:00PM


This is a selfpaced module for students who already have STAT 180 credit but have since determined a need for STAT 190 for their particular degree program. After independently working through the material of STAT 190, you will complete an equivalency exam at the end of the semester to assess statistical competency at the STAT 190 level. Graded on a pass/fail basis.


STAT 19001
Aruni Jayathilaka
TR 2:00PM  3:15PM


Prerequisites: MATH 141 or equivalent.


STAT 19020
Aruni Jayathilaka
T 6:15PM  7:30PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19021
Aruni Jayathilaka
T 3:25PM  4:40PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19022
Aruni Jayathilaka
W 10:25AM  11:40AM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19023
Aruni Jayathilaka
W 4:50PM  6:05PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19024
Aruni Jayathilaka
W 6:15PM  7:30PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19025
Aruni Jayathilaka
W 4:50PM  6:05PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19026
Aruni Jayathilaka
W 2:00PM  3:15PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19027
Aruni Jayathilaka
W 3:25PM  4:40PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19028
Aruni Jayathilaka
W 6:15PM  7:30PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities."


STAT 19029
Aruni Jayathilaka
R 3:25PM  4:40PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19030
Aruni Jayathilaka
R 6:15PM  7:30PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19031
Aruni Jayathilaka
T 4:50PM  6:05PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 19032
Aruni Jayathilaka
R 7:40PM  8:55PM


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities.


STAT 2011
FNU Anudeep Kumar
MW 10:25AM  11:40AM


Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent. MATH 164 recommended. Probability spaces; combinatorial problems; discrete and continuous distributions; independence and dependence; moment generating functions; joint distributions; expectation and variance; sums of random variables; central limit theorem; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MATH 162 and 201 cannot be taken concurrently. This course uses the Tuesday/Thursday 08:0009:30am Common Exam time.


STAT 2012
Mary Cook
MW 2:00PM  3:15PM


Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent. MATH 164 recommended. Probability spaces; combinatorial problems; discrete and continuous distributions; independence and dependence; moment generating functions; joint distributions; expectation and variance; sums of random variables; central limit theorem; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MATH 162 and 201 cannot be taken concurrently. This course uses the Tuesday/Thursday 08:0009:30am Common Exam time.


STAT 2013
–
TR 2:00PM  3:15PM


Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent. MATH 164 recommended. Probability spaces; combinatorial problems; discrete and continuous distributions; independence and dependence; moment generating functions; joint distributions; expectation and variance; sums of random variables; central limit theorem; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MATH 162 and 201 cannot be taken concurrently. This course uses the Tuesday/Thursday 08:0009:30am Common Exam time.


STAT 20301
Javier Bautista
TR 3:25PM  4:40PM


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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.


STAT 20302
Javier Bautista
W 4:50PM  6:05PM


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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.


STAT 20303
Javier Bautista
M 3:25PM  4:40PM


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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.


STAT 20304
Javier Bautista
W 11:50AM  1:05PM


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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.


STAT 20305
Javier Bautista
F 12:30PM  1:45PM


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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.


STAT 2161
Nicholas Zaino
TR 9:40AM  10:55AM


Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent Colocated 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 2162
Bruce Blaine
MW 2:00PM  3:15PM


Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 2163
Aruni Jayathilaka
TR 12:30PM  1:45PM


Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 2181
Joseph Ciminelli
TR 11:05AM  12:20PM


Colocated with STAT 418, STAT 218 Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 twoway and threeway 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 loglinear 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 221W1
Nicholas Zaino
TR 12:30PM  1:45PM


Cross Listed: BST 421, STAT 221W (P) Prerequisites: STAT 180, STAT 190, STAT 212, or STAT 213, and STAT 203 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 27601
Bruce Blaine
MW 10:25AM  11:40AM


Prereq: STAT 212, STAT 180 and STAT 216 (or equivalent) or instructor permission Colisted with STAT 276W, STAT 476 This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations. Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class.


STAT 276W01
Bruce Blaine
MW 10:25AM  11:40AM


Prereq: STAT 212, STAT 180 and STAT 216 (or equivalent) or instructor permission Colisted with STAT 276, STAT 476 This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations. Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class.


STAT 2771
Javier Bautista
TR 9:40AM  10:55AM


Cross Listed: STAT 277 (P), STAT 477 Prerequisites: STAT 216 or STAT 226W. CROSS LISTED with STAT 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 numericallyoriented procedures such as linear models will be included where appropriate. Each student will analyze a reallife 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 290W01
Katherine Grzesik
W 3:25PM  4:40PM


Prerequisites: STAT 203, STAT 216, and one computing course. STAT 217 recommended. This course focuses on the communication skills that help students best discuss and present their professional selves within Statistics. Students will gain experience refining research papers into publicationready formats, constructing meaningful abstracts, and articulating their career and graduate school goals. Through creating a portfolio of materials, including a resume, CV, cover letters, and personal statements, students will refine their ability to communicate their statistical work and goals in preparation for graduate school and the job market, utilizing Microsoft Office, LaTeX, and other fieldspecific software. Students interested in the course should submit a "Course Section PreRequisite Override" request. In this request, include your class year, list the statistics courses that have been taken, and whether you are planning for an internship, job search or graduate school the following year.


STAT 30101
Joseph Ciminelli
TR 2:00PM  3:15PM


Prerequisites: STAT 201, STAT 203, STAT 223 recommended. CSC 171 or equivalent. Statistics is embedded in pop culture through games of chance. In this course, we will explore the probability mechanisms and considerations that go into such games. We will explore relevant probability theory and work our way through calculating odds and outcomes in common games. Students will create virtual programs to simulate outcomes in such games based on our earlier probability work. Throughout the course, we will explore gaming industry standards and ethical considerations.


STAT 3901
–
7:00PM  7:00PM


No description


STAT 390A1
–
7:00PM  7:00PM


No description


STAT 390A2
–
7:00PM  7:00PM


No description


STAT 390A3
Maria McDermott
7:00PM  7:00PM


No description


STAT 390A4
Joseph Ciminelli
7:00PM  7:00PM


No description


STAT 3911
–
7:00PM  7:00PM


Registration for Independent Study courses needs to be completed thru the https://secure1.rochester.edu/registrar/forms/independentstudyform.php instructions for online independent study registration


STAT 3921
–
7:00PM  7:00PM


STAT 392  an online independent study form is available at: https://www.rochester.edu/college/ccas/handbook/independentstudies.html


STAT 3941
–
7:00PM  7:00PM


Registration for Independent Study courses needs to be completed thru the https://secure1.rochester.edu/registrar/forms/independentstudyform.php instructions for online independent study registration


STAT 3951
–
7:00PM  7:00PM


STAT 395  an online independent study form is available at: https://www.rochester.edu/college/ccas/handbook/independentstudies.html Registration for Independent Study courses needs to be completed thru the instructions for online independent study registration.


STAT 4161
Nicholas Zaino
TR 9:40AM  10:55AM


Colocated with STAT 2161 STAT 4161 Prerequisites: STAT 180, STAT 190, 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 4181
Joseph Ciminelli
TR 11:05AM  12:20PM


Colocated with STAT 418, STAT 218 Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 twoway and threeway 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 loglinear 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 47601
Bruce Blaine
MW 10:25AM  11:40AM


Colisted with STAT 276w, STAT 276


STAT 4771
Javier Bautista
TR 9:40AM  10:55AM


Cross Listed: STAT 277 (P), STAT 477 Prerequisites: STAT 216 or STAT 226W. CROSS LISTED with STAT 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 numericallyoriented procedures such as linear models will be included where appropriate. Each student will analyze a reallife 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.

Fall 2024
Number  Title  Instructor  Time 

Monday  
STAT 20303
Javier Bautista


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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. 

Monday and Wednesday  
STAT 2011
FNU Anudeep Kumar


Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent. MATH 164 recommended. Probability spaces; combinatorial problems; discrete and continuous distributions; independence and dependence; moment generating functions; joint distributions; expectation and variance; sums of random variables; central limit theorem; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MATH 162 and 201 cannot be taken concurrently. This course uses the Tuesday/Thursday 08:0009:30am Common Exam time. 

STAT 27601
Bruce Blaine


Prereq: STAT 212, STAT 180 and STAT 216 (or equivalent) or instructor permission Colisted with STAT 276W, STAT 476 This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations. Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class. 

STAT 276W01
Bruce Blaine


Prereq: STAT 212, STAT 180 and STAT 216 (or equivalent) or instructor permission Colisted with STAT 276, STAT 476 This course offers an introduction to statistical computing in the R environment with the goal of exploratory analyses and effective communication using "tidyverse". With a main goal of communicating results to various audiences, this course will require writing via communicating results in a clear and effective manner based on the intended audience. This includes cleaning and preparing data for analysis, exploratory data analyses using simple graphics and tables, acknowledging and working with missing data, advanced graphics including map graphics to communicate results, statistical hypothesis generation & confirmation, introduction to the LaTeX typesetting language, advanced R Markdown formatting techniques (HTML, PDF, Word), figure and table creation with proper adaptive labels and captions, and bibliography with adaptive citations. Basic skills with a test editor (such as Notepad) and Microsoft Excel are assumed. Students are expected to have basic skills in R and RStudio as covered in STAT 212. This course will be held in a computer lab with R and RStudio installed but students will need computer access outside of class. 

STAT 47601
Bruce Blaine


Colisted with STAT 276w, STAT 276 

STAT 18002
Katherine Grzesik


This course is a noncalculus based introduction to statistical analyses that focuses on 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. Calculations are performed with statistical software such as R/RStudio. This course is recommended for students majoring/minoring in statistics, fulfilling premedical requirement, or in the social and natural sciences looking for an applied statistics course that can be used as a foundation for upperlevel methodology courses. Students may earn degree credit for only one of these courses: STAT 180, STAT 190, STAT 212, STAT 213, ECON 230, PSCI 200. 

STAT 2012
Mary Cook


Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent. MATH 164 recommended. Probability spaces; combinatorial problems; discrete and continuous distributions; independence and dependence; moment generating functions; joint distributions; expectation and variance; sums of random variables; central limit theorem; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MATH 162 and 201 cannot be taken concurrently. This course uses the Tuesday/Thursday 08:0009:30am Common Exam time. 

STAT 2162
Bruce Blaine


Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 19021
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19031
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19020
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

Tuesday and Thursday  
STAT 2161
Nicholas Zaino


Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent Colocated 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 2771
Javier Bautista


Cross Listed: STAT 277 (P), STAT 477 Prerequisites: STAT 216 or STAT 226W. CROSS LISTED with STAT 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 numericallyoriented procedures such as linear models will be included where appropriate. Each student will analyze a reallife 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 4161
Nicholas Zaino


Colocated with STAT 2161 STAT 4161 Prerequisites: STAT 180, STAT 190, 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 4771
Javier Bautista


Cross Listed: STAT 277 (P), STAT 477 Prerequisites: STAT 216 or STAT 226W. CROSS LISTED with STAT 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 numericallyoriented procedures such as linear models will be included where appropriate. Each student will analyze a reallife 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 2181
Joseph Ciminelli


Colocated with STAT 418, STAT 218 Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 twoway and threeway 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 loglinear 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 4181
Joseph Ciminelli


Colocated with STAT 418, STAT 218 Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 twoway and threeway 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 loglinear 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 2163
Aruni Jayathilaka


Prerequisites: STAT 180, STAT 190, STAT 212, STAT 213, or equivalent 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 2way ANOVA, contrasts, multiple comparisons, analysis of covariance). This course is noncalculus 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 221W1
Nicholas Zaino


Cross Listed: BST 421, STAT 221W (P) Prerequisites: STAT 180, STAT 190, STAT 212, or STAT 213, and STAT 203 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 19001
Aruni Jayathilaka


Prerequisites: MATH 141 or equivalent. 

STAT 2013
–


Cross Listed: MATH 201 (P), STAT 201 Prerequisites: MATH 162 or equivalent. MATH 164 recommended. Probability spaces; combinatorial problems; discrete and continuous distributions; independence and dependence; moment generating functions; joint distributions; expectation and variance; sums of random variables; central limit theorem; laws of large numbers. MATH 162 (or equivalent) is a strict prerequisite and must be completed before taking 201. MATH 162 and 201 cannot be taken concurrently. This course uses the Tuesday/Thursday 08:0009:30am Common Exam time. 

STAT 30101
Joseph Ciminelli


Prerequisites: STAT 201, STAT 203, STAT 223 recommended. CSC 171 or equivalent. Statistics is embedded in pop culture through games of chance. In this course, we will explore the probability mechanisms and considerations that go into such games. We will explore relevant probability theory and work our way through calculating odds and outcomes in common games. Students will create virtual programs to simulate outcomes in such games based on our earlier probability work. Throughout the course, we will explore gaming industry standards and ethical considerations. 

STAT 20301
Javier Bautista


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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 19022
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 20304
Javier Bautista


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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. 

STAT 19026
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19027
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 290W01
Katherine Grzesik


Prerequisites: STAT 203, STAT 216, and one computing course. STAT 217 recommended. This course focuses on the communication skills that help students best discuss and present their professional selves within Statistics. Students will gain experience refining research papers into publicationready formats, constructing meaningful abstracts, and articulating their career and graduate school goals. Through creating a portfolio of materials, including a resume, CV, cover letters, and personal statements, students will refine their ability to communicate their statistical work and goals in preparation for graduate school and the job market, utilizing Microsoft Office, LaTeX, and other fieldspecific software. Students interested in the course should submit a "Course Section PreRequisite Override" request. In this request, include your class year, list the statistics courses that have been taken, and whether you are planning for an internship, job search or graduate school the following year. 

STAT 18025
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19023
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19025
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 20302
Javier Bautista


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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. 

STAT 18022
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19024
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19028
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities." 

STAT 18010
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

Thursday  
STAT 18011
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18012
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18019
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19029
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18017
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18020
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19030
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18013
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18024
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 19032
Aruni Jayathilaka


This lab accompanies STAT 190 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

Friday  
STAT 18021
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18014
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 20305
Javier Bautista


Cross Listed: MATH 203 (P), STAT 203 Prerequisites: MATH 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. 

STAT 18018
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18023
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18015
Katherine Grzesik


This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. 

STAT 18016
Katherine Grzesik


T This lab accompanies STAT 180 to further explore applying statistical methodology through computing in R. Students must register for a lab when registering for the main lecture. Please plan on bringing a personal laptop with you to complete the computing activities. I 200. 