Course Descriptions

For your first course in statistics, please see the Placement Information before registering.

Course Number Course Name and Description
STA 30 (10)

Basic Statistics and Quantitative Literacy

Statistical concepts involved in making inferences, decisions, and predictions from data. Emphasis on applications, not formal technique. Instructor: Staff

Prerequisites: Must have taken placement test and placed accordingly

Typically offered: Fall, Spring and Summer

STA 89S (49S)

First Year Seminar

Topics vary each semester offered. Instructor: Staff

Prerequisites: First year and Transfer students only

Audience: Introductory

Typically offered: Spring Only

STA 101 (101)

Data Analysis and Statistical Inference

Introduction to statistics as a science of understanding and analyzing data. Major themes include data collection, exploratory analysis, inference, and modeling. Focus on principles underlying quantitative research in social sciences, humanities...

Prerequisites: Placement exam

Typically offered: Fall, Spring and Summer

STA 102 (102)

Intro Biostatistics

Reading and interpretation of statistical analyses from life science and medical literature. Topics include: basic concepts and tools of probability and conditional probability, independence, two-by-two tables, Simpson's paradox, medical...

Prerequisites: Must have STA 30 (10) or sufficient score on placement exam

Typically offered: Fall and/or Spring

STA 110FS (80FCS)

Focus Program - Introductory Special Topics in Statistics

This is a seminar course for focus students. Topics vary every semester.

Prerequisites: Math 31 (21) is required.

Audience: Introductory

Typically offered: Occasionally

STA 111 (103)

Probability/Stat Inference

Basic laws of probability, random events, independence and dependence, expectations, Bayes theorem. Discrete and continuous random variables, density, and distribution functions. Binomial and normal models for observational data. Introduction to...

Prerequisites: MATH 21 (31)

Typically offered: Fall and/or Spring

STA 130 (113)

Probability/Statistics In Engineering

Introduction to probability, independence, conditional independence, and Bayes' theorem. Discrete and continuous, univariate and multivariate distributions. Linear and nonlinear transformations of random variables. Classical and Bayesian...

Prerequisites: MATH 212 (103) or equivalent

Typically offered: Fall and/or Spring

STA 210 (121)

Regression Analysis

Extensive study of regression modeling. Multiple regression, weighted least squares, logistic regression, log-linear models, analysis of variance, model diagnostics and selection. Emphasis on applications. Examples drawn from a variety of fields...

Prerequisites: 100-level STA course.

Typically offered: Fall and/or Spring

STA 230 (104)

Probability

Probability models, random variables with discrete and continuous distributions. Independence, joint distributions, conditional distributions. Expectations, functions of random variables, central limit theorem. Instructor: Staff

Prerequisites: MATH 202 (102) MATH 212 (103) or MATH 222 (105)

Typically offered: Fall and/or Spring

STA 250 (114)

Statistics

An introduction to the concepts, theory, and application of statistical inference, including the structure of statistical problems, probability modeling, data analysis and statistical computing, and linear regression. Inference from the...

Prerequisites: MATH 221 (104) and STA 230 (104)/MATH 230 (135)

Typically offered: Fall and/or Spring

STA 320 (130)

Design and Analysis of Causal Studies

Design of randomized experiments and observational studies. Role of randomization, block designs, factorial designs, fractional factorial designs, matching. Analysis of variance, contrasts, propensity score matching, instrumental variables. ...

Prerequisites: STA 210 (121)

Typically offered: Occasionally

STA 321 (135)

Statistics Of Surveys

Design and analysis of surveys, including random sampling, stratification, clustering, and multi-stage sampling. Design-based and model-based inference. Methods for handling missing data. Instructor: Reiter

Prerequisites: STA 210 (121)

Typically offered: Occasionally

STA 340 (140)

Introduction to Statistical Decision Analysis

Quantitative methods for decision making under uncertainty. Probability theory, personal probabilities and utilities, decision trees, ROC curves, sensitivity analysis, dominant strategies, Bayesian networks and influence diagrams, Markov models...

Prerequisites: STA 230 (104)

Typically offered: Occasionally

STA 350S (180S)

Statistical Methods in Bioinformatics

Statistical and analytical tools for bioinformatics and genomics. Methods for comparison, database search, and functional inference for DNA, RNA, and protein sequences; analysis of families of molecular sequences and structures; inference in...

Prerequisites: Statistical Science 230 (104) required. Statistical Science 250 (114) Computer programming and molecular biology required.

Typically offered: Occasionally

STA 360 (122)

Bayesian And Modern Statistics

Principles of data analysis and advanced statistical modeling. Bayesian inference, prior and posterior distributions, multi-level models, model checking and selection, stochastic simulation by Markov Chain Monte Carlo. Instructor: Clyde, Reiter...

Prerequisites: STA 230 (104) , STA 250 (114), and STA (210) 121 (or equivalent)

Typically offered: Fall and/or Spring

STA 393 (191)

Research Independent Study

Individual research in a field of special interest, under the supervision of a faculty member, resulting in a substantive paper or written report containing significant analysis and interpretation of a previously approved topic. Consent of...

Prerequisites: None

Typically offered: Fall and/or Spring

STA 470S (145S)

Introduction to Statistical Consulting

Participation by students in data analysis projects from the DSS Statistical Consulting Center. Projects led and directed by DSS faculty. Instructor: Lucas

Prerequisites: STA 360 (122)

Typically offered: Fall and/or Spring

STA 471S (175S)

Computational Data Analysis

Data analysis, exploration, and representation. Scientific modeling and computation. Data mining for large datasets, algebraic decomposition methods, stochastic simulation for temporal models of dynamic processes, graphical and network data,...

Prerequisites: STA 360 (122)

Typically offered: Spring Only

STA 490S (393)

Special Topics in Statistics

Special topics not covered in core courses and more advanced topics related to current research directions in statistics.  Consent of instructor required.

Prerequisites: None

Typically offered: Occasionally

STA 497S (190AS)

Research Seminar in Statistical Science I

Statistical and mathematical underpinnings of methodological research in statistical science. Student presentations of their statistical research in collaboration with, and under the supervision of, an DSS faculty mentor.

Prerequisites: None

Typically offered: Fall Only

STA 498S (190)

Research Seminar in Statistical Science II

Continuation of Statistics 497S (190AS). Statistical and mathematical underpinnings of methodological research in statistical science. Student presentations of their statistical research in collaboration with, and under the supervision of, a DSS...

Prerequisites: STA 497S (STA 190AS)

Typically offered: Spring Only

STA 613 (270)

Statistical Methods/Computational Biology

Methods of statistical inference and stochastic modeling with application to functional genomics and computational molecular biology.

Prerequisites: STA 611 (213). linear algebra, and multivariate calculus