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Probability and Statistic Courses for Major

Stat 3601. Statistics and Probability for Science and Engineering I (4)

Basic probability rules (independence, Bayes' Theorem), distributions (binomial, Poisson, normal, exponential), reliability. Descriptive, inferential statistics (control charts, estimation, hypothesis testing: one, two samples), correlation, regression. Emphasizes: computer analysis, simulation; science, engineering applications. Not open to those with credit for Stat/Engr/Math 3502. (Cross-listed with Engr 3601). Prerequisite: Math 1305.

Note: Stat 3601 is the preferred choice.

Stat 3401. Introduction to Probability Theory I (4)

The theory of probability with applications to science and engineering. Sample spaces; random variables; joint, marginal, conditional distributions; expectations; important distributions (binomial, Poisson, normal, etc.); and moment generating functions. (Cross-listed with Math 3401.) Prerequisite or concurrent: Math 1305

Stat 3502. Statistical Inference I (4)

Random variables, sampling distributions (binomial, Poisson, normal, exponential), conditional probability. Estimation, hypothesis testing. Computer-aided computations. Topics include: t-tests; correlation, regression; proportions, chi-squared; ANOVA. (Cross-listed with Math 3502.) Prerequisite: Math 1305 or Math 1820