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**STAT 101. Principles of Statistics.** (Fall 2014: , Spring 2014: [Evaluations](/images/other/2014_spring_evaluations_shum.pdf)
Statistical concepts in modern society; descriptive statistics and graphical displays of data; the normal distribution; data collection (sampling and designing experiments); elementary probability; elements of statistical inference; estimation and hypothesis testing; linear regression and correlation; contingency tables.
**STAT 104. Introduction to Statistics.** (Fall 2012, Spring 2013)Statistical concepts and their use in science; collecting, organizing and drawing conclusions from data; elementary probability; binomial and normal distributions; regression; estimation and hypothesis testing. For students in the agricultural and biological sciences.
**STAT 226. Introduction to Business Statistics I.** (Fall 2013)
Obtaining, presenting, and organizing statistical data; measures of location and dispersion; the Normal distribution; sampling and sampling distributions; elements of statistical inference; estimation and confidence intervals; hypothesis testing; inference for simple linear regression analysis; use of computers to visualize and analyze data.
**STAT 330. Probability and Statistics for Computer Science.** (Fall 2012)
Topics from probability and statistics applicable to computer science. Basic probability; Random variables and their distributions; Stochastic processes including Markov chains; Queuing models; Basic statistical inference; Introduction to regression.
**STAT 401. Statistical Methods for Research Workers.** (Spring 2013, Summer 2012)
Graduate students without an equivalent course should contact the department. Methods of analyzing and interpreting experimental and survey data. Statistical concepts and models; estimation; hypothesis tests with continuous and discrete data; simple and multiple linear regression and correlation; introduction to analysis of variance and blocking.
**MATH 307 Linear Algebra and Differential Equations.**
Introduction to linear algebra, application of eigenvalue techniques to the solution of differential equations.