# Courses

#### Courses currently being offered:

Fall >
Spring >

Check the course schedules/descriptions available via the Registrar's Office for the official schedules for the widest range of terms for which such information is available.

### Course Catalog

Below you will find a list of all courses that have been offered.
NOTE: Not all of these courses are offered in any given year.

STT 201 INTRODUCTION TO PROBABILITY

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.

Prerequisites: MTH 162 or equivalent, MTH 164 recommended. Same as STT 201.
Last Offered: Fall 2019

STT 202 INTRODUCTION TO STOCHASTIC PROCESSES

Theory and applications of random processes, including Markov chains, Poisson processes, birth-and-death processes, random walks. Prerequisite: STT 201. Same as MTH 202.

STT 203 INTRODUCTION TO MATHEMATICAL STATISTICS

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.

Prerequisites: STT 201 or familiarity with the elementary principles of probability, expected value, variance and covariance.
Last Offered: Fall 2019

STT 211 Statistical Literacy and Applied Methodolog

This course is a non-calculus 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.

Last Offered: Fall 2019

STT 212 APPLIED STATISTICS I

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

Last Offered: Fall 2019

STT 213 ELEMENTS OF PROBABILITY & MATHEMATICAL STATISTICS

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.

Prerequisites: MTH 141 or equivalent.
Last Offered: Fall 2019

STT 214 BIOSTATISTICS

No description

Last Offered: Spring 2019

STT 214W BIOSTATISTICS WRITING

No description

Last Offered: Spring 2019

STT 216 APPLIED STATISTICS II

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.

Prerequisites: STT 211, STT 212, or STT 213
Last Offered: Fall 2019

STT 218 CATEGORICAL DATA ANALYSIS

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.

Last Offered: Fall 2019

STT 219 NONPARAMETRIC INFERENCE

No description

Last Offered: Fall 2019

STT 221W SAMPLING TECHNIQUES

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.

Prerequisites: STT 211, STT 212 or STT 213, and 203 or equivalent.
Last Offered: Fall 2019

STT 223 INTRO. TO BAYESIAN INFERENCE

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.

Prerequisites: STT 203 and MTH 164, or instructor permission
Last Offered: Spring 2019

STT 226W INTRODUCTION TO LINEAR MODELS

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.

Prerequisites: STT 211, STT 212 or 213, and STT 203 or equivalent..
Last Offered: Spring 2019

STT 262 COMP INTRO TO STATISTICS

No description

Last Offered: Fall 2019

STT 276 STATISTICAL COMPUTING IN R

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 built-in 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.

Prerequisites: STT 211, 212, 213, or equivalent
Last Offered: Spring 2019

STT 277 COMPUTING, INTRODUCTION TO STATISTICAL SOFTWARE

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.

Prerequisites: STT 211, STT 212 or STT 213 and STT 216 or STT 226W. CROSS LISTED with STT 477.
Last Offered: Fall 2019

STT 278

No description

Last Offered: Fall 2012

STT 391 INDEPENDENT STUDY

No description

Last Offered: Fall 2019

STT 391W INDEPENDENT STUDY

No description

Last Offered: Spring 2019

STT 395 RESEARCH IN STATISTICS

No description

Last Offered: Fall 2019

STT 477 INTRO STATISTICAL SOFTWARE I

No description

Last Offered: Fall 2019

STT 478 INTRO STATISTICAL SOFTWRE II

No description

Last Offered: Fall 2012