STAT 415 follows the content covered in STAT 414 and focuses on the theoretical treatment of statistical inference, including sufficiency, estimation, hypothesis testing, regression, analysis of variance, chi-square tests, and nonparametric methods. The course goals are:
- To develop a theoretical understanding of estimation.
- To develop a theoretical understanding of hypothesis testing.
- To develop a theoretical understanding of nonparametric methods.
- To develop a theoretical understanding of basic Bayesian methods.
A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests.
Dr. Laura Simon is the primary author of the materials for this course and has taught this course in residence several semesters.
Students must have immediate access to a printer/scanner in order to scan hand written assignments into .pdf documents and upload them into Canvas.
Access to the Minitab 17 statistical software package. (Although you will actually be allowed to use any of the other mainstream statistical packages, such as SAS, SPSS, and R, the methods in the course will be demonstrated only using Minitab.) See the Statisitical Software page for more information.
Hogg, R.V., and Tanis, E.A. (2020). Probability and Statistical Inference, 10th Edition, Pearson. ISBN-978-0135189399: We will primarily cover chapters 6-10.
Note: This is NOT the global edition.
*10th adopted for SU19
The only official requirement is having successfully completed STAT 414. However, if you had trouble with any of the calculus methods used in STAT 414, such as differentiation, integration, series, and limits, you might want to review these methods again before the course begins.