ISM 421Predictive Data Modeling
In this course students will learn how to use business applications involving explanatory and response variables requiring advanced statistical models that go beyond inferential tools such as confidence intervals and hypothesis testing. Students will learn to use advanced multivatiate regresson analysis of variance and residual diagnostics, logistic regression analysis of variance (ANOVA), multiple analysis of variance (MANOVA), time series modeling, and analysis of categorical variables. Students will use advanced statistical packages such as Excel, Python, R, and/or SPSS to complete various projects including computation and graphing. It is assumed that students have mastery introductory statistics topics including descriptive tools, inference, and ordinary least squares. Prerequisites: ISM 331
Level | Undergraduate |
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Credits | 3 |
Lab fee | None |
Pre-requisites | ISM 331 |
Course offerings
Please contact the registrar for details on course availability.