Credit Hours: 3
Learning Objective: Provide the students with the fundamentals of probability, statistical methods, and data analysis.
Description: Descriptive statistics; elementary probability; sampling distributions; inference, testing hypotheses, and estimation; normal, binomial, Poisson, hypergeometric distributions; one-way analysis of variance; contingency tables; regression.
Topics Covered: Data (sample vs. Population, histograms, sample mean, median, variance, standard deviation), Elementary probability (axioms, basic rules; little attention to counting and conditional probability), Random variables (discrete vs. Continuous, moments), Binomial, hypergeometric, Poisson distributions, Poisson approximation to binomial, Normal distribution, normal approximation to binomial, Sampling distributions, distribution of mean, central limit theorem, Confidence intervals for means, Confidence intervals for proportions, Tests of hypotheses for means and proportions, Regression and correlation, One way analysis of variance, Contingency tables
Prerequisites: Calculus. Integration and differentiation of functions of one variable and two variables.
Applied / Theory: 45 / 55
Web Address: http://www.stat.purdue.edu/~xbw/courses/stat511/511.htm
Web Content: Course information, syllabus, homework assignments, lecture notes, and announcements will be posted to course website (undecided); a login and password will be provided.
Homework: Weekly assignments. Homework solutions will be released on Blackboard.
Projects: No project will be required for this course. However, some computer-related homework will be assigned.
Exams: There is one midterm and one final exam.
Textbooks: Probability and Statistics for Engineering and the Sciences; Purdue University, Cengage; ISBN 9781305745858
Computer Requirements: Computer/phone/tablet can NOT be used on the homework assignments, unless it states computer assignments. Calculator is allowed on the homework assignments, and is highly recommended on the exams. A free statistical software, R, will be used in the course, which can be downloaded from CRAN (cran.r-project.org). I will use both Blackboard and my website.
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