2014-15 Undergraduate Academic Catalog

*To download a sample syllabus, click here.*

An introduction to concepts in statistics at a deeper quantitative level than that offered in MTH 110. This course emphasizes rationales, applications and interpretations using advanced statistical software. Examples are drawn primarily from economics, education, psychology, sociology, political science, biology and medicine. Topics include introductory design of experiments, data acquisition, graphical exploration and presentation, descriptive statistics, one- and two-sample inferential techniques, simple/multiple regression, goodness of fit and independence, one-way/two-way analysis of variance (ANOVA). Written reports link statistical theory and practice with communication of results. Recommended for students pursuing quantitatively-based careers. Prerequisites: MTH 110, MTH 151, placement exemption or permission of the statistics program coordinator. Offered fall and spring.

An introduction to the concepts and methods of statistical reasoning associated with sample surveys. This course emphasizes rationales, applications and interpretations of sampling strategies used for estimation. Advanced statistical software such as SAS or SPlus may be used. Case studies of survey methods are drawn primarily from the social sciences while field sampling applications to ecological and environmental research may be used. Topics include survey design issues, simple random sampling, stratified sampling, single and two stage cluster sampling, systematic sampling, parameter estimation and sample size calculation. Written reports link statistical theory and practice with communication of results. Prerequisite: MTH 110, MTH 220/STS 212 or permission of the statistics program coordinator.

Offered fall of odd-numbered years.

Offered fall of odd-numbered years.

This course emphasizes rationales, applications and interpretations of regression methods using a case study approach. Advanced statistical software such as SAS or SPlus may be used. Topics include simple linear regression, multiple linear regression, indicator variables, robustness, influence diagnostics, model selection, logistic regression for dichotomous response variables and binomial counts and non-linear regression models. Written reports link statistical theory and practice with communication of results. Prerequisite: MTH 220/STS 212 or permission of the statistics program coordinator. Offered spring of even-numbered years.

This course focuses on data-oriented approaches to statistical estimation and inference using techniques that do not depend on the distribution of the variable(s) being assessed. Topics include classical rank-based methods, as well as modern tools such as permutation tests and bootstrap methods. Advanced statistical software such as SAS or SPlus may be used, and written reports will link statistical theory and practice with communication of results. Prerequisite: MTH 220/STS 212 or permission of the statistics program coordinator. Offered spring of odd-numbered years.

This course explores methods of designing and analyzing scientific experiments to address research questions. Emphasis is placed on statistical thinking and applications using real data, as well as on the underlying mathematical structures and theory. Topics include completely randomized designs, randomized block designs, factorial treatment designs, hierarchical designs, split-plot designs and analysis of covariance. Advanced statistical software such as SAS or SPlus may be used, and written reports will link statistical theory and practice with communication of results. Prerequisite: MTH 220/STS 212 or permission of the statistics program coordinator. Offered fall of even-numbered years.

An intermediary course in statistical computing using both R and SAS software. This course introduces the software R with an emphasis on utilizing its powerful graphics and simulation capabilities. This course also emphasizes issues with messy data entry, management, macro writing, and analysis using SAS software. Topics include using computer software for data entry, sub-setting data, merging data sets, graphical descriptive statistics, numerical descriptive statistics, macros, standard statistical analysis using SAS and R, creating functions in R and simulations in R. Prerequisite: MTH 220/STS 212, or permission of the statistics program coordinator. Offered Winter Term.

Topics include axiomatic probability, counting principles, discrete and continuous random variables and their distributions, sampling distributions, central limit theorem, confidence intervals and hypothesis testing. Prerequisite: MTH 251. Offered fall of even-numbered years.

This course offers an introduction to theoretical concepts in mathematical statistics. Topics include introduction to the limit theorems and the theory of point estimation, interval estimation, tests of hypotheses and likelihood ratio tests. Although this is primarily a proofs-based course, advanced statistical software such as SAS or R may be used. Prerequisites: MTH 220/STS 212, MTH 251, and MTH 329/STS 341 or permission of the statistics program coordinator. Offered spring of odd-numbered years.

This course prepares mathematics and statistics majors for Seminar II, the capstone seminar, by instruction and experience in library research and formal oral presentations on advanced mathematical and statistical topics selected by the instructor and students. Prerequisite: Junior/senior standing or permission of the department. Offered spring.

In this capstone experience for senior mathematics and statistics majors, students conduct extensive research on a mathematical or statistical topic and formally present their work in writing and orally. Course requirements may include a satisfactory score on the ETS major field achievement test depending on major. Prerequisite: MTH/STS 361 and junior/senior standing or permission of the department. Offered fall.

The internship provides advanced work experiences in some aspect of statistical science and is offered on an individual basis when suitable opportunities can be arranged. Prerequisite: permission of the statistics program coordinator.

Students engage in independent research or consulting related to the field of statistics. Research is conducted under supervision of statistics faculty. Prerequisite: Permission of the statistics program coordinator.

This page was updated July 2, 2014.