A Simchi

STAT 151 - Introduction to Applied Statistics I

Data collection and presentation, descriptive statistics. Probability distributions, sampling distributions and the central limit theorem. Point estimation and hypothesis testing. Correlation and regression analysis. Goodness of fit and contingency table. Prerequisite: Mathematics 30-1 or 30-2. Note : This course may not be taken for credit if credit has been obtained in any STAT course, or in KIN 109, PEDS 109, PSYCH 211, SCI 151 or SOC 210.

STAT 161 - Introductory Statistics for Business and Economics

Data collection and presentation, descriptive statistics. Probability distributions, sampling distributions and the central limit theorem. Point estimation and hypothesis testing. Correlation and regression analysis. Goodness of fit and contingency table. Use of a microcomputer software package for statistical analyses in business and economics. Prerequisite: Mathematics 30-1 or 30-2. This course may not be taken for credit if credit has been obtained in any STAT course, or in KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210.

STAT 235 - Introductory Statistics for Engineering

Descriptive data analysis. Calculus of Probability. Binomial, multinomial, Poisson, normal, beta, exponential, gamma, hypergeometric, and Weibull distributions. Sampling distributions. Estimation, testing hypotheses, goodness-of-fit tests, and one-way analysis of variance. Linear correlation and regression. Sampling. Quality control. Use of a microcomputer software package for statistical analyses in engineering applications. Prerequisite: MATH 100. Corequisite: MATH 101. Notes: (1) This course may not be taken for credit if credit has already been obtained in one of STAT 141, 151, 222, 265, 266; PSYCH 211, SCI 151 or SOC 210. (2) Intended for Engineering students. Other students who take this course will receive *3.0.

STAT 266 - Probability and Statistics II

Functions of random variables, sampling distributions, Central Limit Theorem, law of large numbers, statistical models for the data, likelihood, parameters and their interpretation, objectives of statistical inference, point and interval estimation, method of moments, basic notions of testing of hypotheses, errors of the first and second kind, significance level, power, p-value. Prerequisites: one of MATH 209, MATH 214, or MATH 217 and one of STAT 265 or MATH 281. Corequisites: One of MATH 225 or 227. Credit can only be obtained in one of STAT 266 or STAT 276.

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