Although it is not yet possible to have an undergraduate major in Statistics, there are many opportunities for undergraduates to learn about statistics as a possible career or as a complement to other majors.

Students interested in focusing on statistics are encouraged to consider a minor in Statistics along with a major in a field of interest. The minor in Statistics is designed to provide students with exposure to both statistical theory and practice.

Statistics Department's undergraduate offerings:

Stats 7: Basic Statistics

Introduces basic inferential statistics including confidence intervals and hypothesis testing on means and proportions, t-distribution, Chi Square, regression and correlation. F-distribution and nonparametric statistics included if time permits.

Stats 8: Introduction to Biostatistics

This course teaches introductory statistical techniques used to collect and analyze experimental & observational data from health sciences and molecular, cellular, environmental and evolutionary biology. Specific topics include exploration of data, producing data, probability & sampling distributions, basic statistical inference for means, proportions, linear regression & analysis of variance

Stats 67: Introduction to Probability and Statistics for Computer Science

Introduction to the basic concepts of probability and statistics with discussion of applications to computer science. Specific topics include axioms of probability, random variables, expectation and variance, joint distributions, and elementary statistical inference.

Stats 110: Statistical Methods for Data Analysis I

Introduction to statistical methods for analyzing data from experiments and surveys. Methods covered include two-sample procedures, analysis of variance, simple and multiple linear regression.

Stats 111: Statistical Methods for Data Analysis II

Introduction to statistical methods for analyzing data from surveys or experiments. Emphasizes application and understanding of methods for categorical data including contingency tables, logistic and Poisson regression, loglinear models.

Stats 112: Statistical Methods for Data Analysis III

Introduction to statistical methods for analyzing longitudinal data from experiments and cohort studies. Topics covered include survival methods for censored time-to-event data, linear mixed models, non-linear mixed effects models, and generalized estimating equations.

Stats 115: Introduction to Bayesian Analysis

Course presents the basics of Bayesian concepts and methods with emphasis on data analysis. Special emphasis on specification of prior distributions. Development for one-two samples and on to binary, Poisson and linear regression. Analyses performed using free OpenBugs software.

Stats 120A: Introduction to Probability and Statistics

This is the first of a three-quarter upper division calculus-based introduction to probability and statistics. This course introduces probability and random

Stats 120B: Introduction to Probability and Statistics

This is the second of a three-quarter upper division calculus-based introduction to probability and statistics. This course introduces the key ideas in statistical inference including point estimation, confidence intervals and significance testing.

Stats 120C: Introduction to Probability and Statistics

This is the third of a three-quarter upper division calculus-based introduction to probability and statistics. This course introduces two sample methods, categorical data analysis, linear regression analysis.

Stats 140: Multivariate Statistical Methods

Theory and application of multivariate statistical methods. Topics include: statistical inference for the multivariate normal model and its extensions to multiple samples and regression, use of statistical packages for data visualization and reduction, discriminant analysis, cluster analysis, and factor analysis.