Skip to content

Predictive Modeling builds on initial data preparation, cleaning, and analysis, enabling students to make assertions vital to organizational needs. In this course, students conduct logistic regression and multiple regression to model the phenomena revealed by data. The course covers normality, homoscedasticity, and significance, preparing studen…

Notifications You must be signed in to change notification settings

MikeMMattinson/Predictive_Modeling_D208

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

54 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Predictive_Modeling_D208

Predictive Modeling builds on initial data preparation, cleaning, and analysis, enabling students to make assertions vital to organizational needs. In this course, students conduct logistic regression and multiple regression to model the phenomena revealed by data. The course covers normality, homoscedasticity, and significance, preparing students to communicate findings and the limitations of those findings accurately to organizational leaders. Exploratory Data Analysis is a prerequisite for this course.

About

Predictive Modeling builds on initial data preparation, cleaning, and analysis, enabling students to make assertions vital to organizational needs. In this course, students conduct logistic regression and multiple regression to model the phenomena revealed by data. The course covers normality, homoscedasticity, and significance, preparing studen…

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages