STAT Statistics

STAT-130 Elementary Statistics 2 cr.
ANRSN STAT

Fall, Spring and Summer
Concepts and application of probability and statistics: data analysis (graphical displays, numerical summary measures); probability and probability distributions; concepts of statistical inference (estimation and hypothesis testing). Illustrated with output from statistical computing packages.

STAT-320 Statistical Methods 3 cr.
ANRSN STAT

Fall and Spring
Methods of describing data: graphical methods, numerical summary measures, exploratory data analysis. Probability, probability distributions, expected value. Sampling distributions. Statistical inference: estimation and hypothesis testing for one-sample and two-sample problems. Regression analysis. Demonstrating with standard statistical software packages.

STAT-330 Probability and Statistics for Engineering and the Sciences 3 cr.
Fall and Spring
Exploratory data analysis; basic probability, probability distributions, mathematical expectation, sampling distributions; basic statistical inference (estimation and hypothesis testing); topics in reliability.

Prerequisites: take MATH-154 or MATH-157.

STAT-331 Probability and Mathematical Statistics I 3 cr.
Fall
Sample spaces. Probability functions for discrete and continuous sample spaces. Conditional probability and independence. Random variables; probability density and cumulative distribution functions; joint, marginal, and conditional distributions. Expected values, moments, and moment-generating functions. Binomial, hypergeometric, Poisson, normal, and gamma distributions.

Prerequisites: take MATH-154 or MATH-157. Corequisite: Math-158.

STAT-332 Probability and Mathematical Statistics II 3 cr.
Spring
Point estimation. Properties of point estimators: unbiasedness, efficiency, consistency, sufficiency. The method of maximum likelihood. Basic concepts of interval estimation and hypothesis testing. Inference in one-sample and two-sample problems. Simple linear regression analysis; the method of least squares. Goodness-of-fit tests. Analysis of categorical data.

Prerequisites: take STAT-331.

STAT-337 Design of Experiments I 2 cr.
Fall
Linear and curvilinear regression, single-factor designs, confidence ellipsoids for means, blocking, Latin and other squares, factorial designs.

Prerequisites: take STAT-332.

STAT-338 Design of Experiments II 2 cr.
Spring
Fixed-effect, random-effect and mixed models; nested and nested-factorial designs, split-plot designs, confounding in blocks, analysis of convariance, response surfaces, sequential analysis.

Prerequisites: take STAT-337.

STAT-440 Advanced Linear Modeling-Regression and Time Series Analysis 3 cr.

Fall and Spring

Multiple regression, inference about regression parameters, remedical regression measures, quantitative and qualitative regression, model selection/validation, nonlinear regression, neural networks, logistic and Poisson regression, generalized linear models, time series, smoothing, stochastic time series, moving average and autoregressive models, auto regressive integrated moving average (ARIMA), estimating and forecasting with time series.

Prerequisites: take STAT-332.