Paul Cartledge

MATH 154 - Calculus for Business and Economics I

The derivative as a rate of change. Differentiation of elementary, trigonometric, exponential, and logarithmic functions. The definite integral as a summation. Integration. The Fundamental Theorem of Calculus. Optimization. Applications in the context of business and economics. Prerequisite: Mathematics 30-1. Note: Credit can be obtained in at most one of MATH 100, 113, 114, 117, 134, 144, 154 or SCI 100.

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, confidence intervals and hypothesis testing. Correlation and regression analysis. ANOVA. 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. Notes: (1) Credit can be obtained in at most one of STAT 151, STAT 161, and STAT 235. (2) This course may not be taken for credit if credit has been obtained in obtained in STAT 222, STAT 266, STAT 276, 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, normal, and exponential distributions. Sampling distributions. Estimation, testing hypotheses, and one-way analysis of variance. Linear correlation and regression. Sampling. 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 151, 161, 222, 265, 266, 276, 281; KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210. (2) Intended for Engineering students. (2) Intended for Engineering students. Other students who take this course will receive 3.0 units.

STAT 235B - 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 151, 161, 222, 265, 266, 276, 281; KIN 109, PEDS 109, PSYCH 211, PTHER 352, SCI 151 or SOC 210. (2) Intended for Engineering students. (2) Intended for Engineering students. Other students who take this course will receive 3.0 units.

STAT 265 - Probability and Statistics I

Sample space, events, combinatorial probability, conditional probability, independent events, Bayes Theorem, random variables, discrete random variables, expected values, moment generating function, inequalities, continuous distributions, multivariate distributions, independence. Corequisite: One of MATH 209, 214 or 217. Note: Credit can be obtained in at most two of STAT 181, STAT 281, or STAT 265.

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