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Statistics Courses (STA)

GE Core denotes General Education Core credit;
GE Marker
denotes General Education Marker credit;
CAR denotes College Additional Requirement credit.

Courses for Undergraduates

108 Elementary Introduction to Probability and Statistics (3:3)

GE Core: GMT

May not be taken for credit by students who have received credit for ECO 250 or 350 or who are concurrently enrolled in ECO 250.

Survey of statistics intended for undergraduates in any discipline. Graphical displays, numerical measures, relationships between variables, elements of good data collection. Basic probability, introduction to inferential techniques including confidence intervals and significance testing. Emphasis on statistical literacy. (Fall & Spring)

271 Fundamental Concepts of Statistics (3:3)

Pr. grade of at least C in MAT 119 or 150 or STA 108 or permission of department

Survey of basic descriptive and inferential statistics. Graphs and descriptive measures, simple linear regression and correlation, data collection, basic probability and probability models, interval estimation and significance testing, analysis of variance, use of statistical software. An appropriate preparation for more advanced statistics courses in any discipline. (Fall & Spring)

290 Introduction to Probability and Statistical Inference (3:3)

Pr. MAT 292 or permission of instructor

Introduction to probability models and statistical inference. Descriptive statistics, basic probability laws, discrete and continuous probability models, sampling distributions, central limit theorem, estimation, hypothesis testing, simple regression, and correlation. (Fall or Spring)

291 Statistical Methods (3:3)

Pr. 271 or 290 or permission of instructor

Two-group comparisons, simple and multiple regression, one and two factor ANOVA, categorical data analysis, nonparametric methods. (Spring)

351 Probability (3:3)

Pr. grade of at least C in MAT 292

Basic probability theory; combinatorial probability, conditional probability and independent events; univariate and multivariate probability distribution functions and their properties. (Fall)

352 Statistical Inference (3:3)

Pr. grade of at least C in STA 290 or permission of instructor

Descriptive and inferential statistics. Emphasis on sampling distributions; theory of estimation and tests of hypotheses, linear hypothesis theory, regression, correlation and analysis of variance. (Spring)

375 Statistical Data Mining (3:3)

Pr. grade of at least C in STA 291

Introduction to statistical methods for data mining; classification and prediction methods using regression and discrimination techniques; clustering methods using distance, linkage, hierarchical methods. Using statistical software to perform data mining.

382 Introduction to Sampling Methods (3:3)

Pr. STA 291 or permission of instructor

Designing survey instruments; estimation of population mean, total, and proportion using simple random, stratified, systematic, and cluster sampling; other sampling techniques such as pps sampling and randomized response methods. (Alt)

383 Introduction to Nonparametric Methods (3:3)

Pr. STA 291 or permission of instructor

One and two sample permutation and rank tests, k-sample tests, tests of association, contingency table analysis, nonparametric bootstrapping. (Alt)

481 Introduction to Design of Experiments (3:3)

Pr. STA 291 or permission of instructor

Planning and analysis of experimental and observational studies. Completely randomized, blocked, split-plot, and repeated measures designs. Factorial arrangements and interaction. Power and sample size calculation. (Alt Years)

482 Introduction to Time Series Models (3:3)

Pr. STA 352 or permission of instructor

Estimation/removal of trend and seasonality, introduction to stationary stochastic processes, fitting ARMA/ARIMA models, forecasting techniques, miscellaneous topics, and introduction to a time series modeling software package. (Alt Years)