MATH 341 - Applied Statistical Methods I

5 CR

This class covers probability theory and applications including trees and Venn diagrams, conditional probability, contingency tables, independence and Bayes theorem. It will cover random variables and sampling distributions (binomial, Poisson, normal, exponential, geometric and hypergeometric ) and their use in confidence intervals and hypothesis testing such as t-tests, z-tests, one and two sample mean and proportions, chi-squared; ANOVA. The focus will be on real world examples from a variety of sources and using statistical software such as Excel, Minitab, SAS or R. Students should expect to produce reports and presentations.

Prerequisite(s): BA 240 with a C or better and admission into Data Management and Analysis BAS, Data Analytics Concentration program, or permission of the instructor.

Course Outcomes
Formulate a real world problem into the appropriate statistical model Calculate probabilities using the appropriate rule, table or diagram Classify the sampling distributions and calculate probabilities Choose appropriate calculations for a confidence interval or a hypothesis test Perform calculations with and without technological tools Perform appropriate ANOVA model Interpret results and clearly state conclusions in reports and presentations with close attention to detail

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