Data Analysis and Interpretation Specialization
Course Features
Duration
5 months
Delivery Method
Online
Available on
Limited Access
Accessibility
Desktop, Laptop
Language
English
Subtitles
English
Level
Beginner
Effort
3 hours per week
Teaching Type
Self Paced
Course Description
Course Overview
Virtual Labs
International Faculty
Post Course Interactions
Instructor-Moderated Discussions
Case Studies, Captstone Projects
Skills You Will Gain
What You Will Learn
Learn to develop a research question, describe the variables and their relationships, calculate basic statistics, and present your results clearly
Use powerful data analysis tools – either SAS or Python – to manage and visualize your data, including how to deal with missing data, variable groups, and graphs
Learn a variety of statistical tests, as well as strategies to know how to apply the appropriate one to your specific data and question
Learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression modelLearn how to apply, test, and interpret machine lear
Course Instructors
Lisa Dierker
Professor
Jen Rose
Research Professor