Advanced Regression Topics in Excel
Estimated Time Commitment: 5 Hours
Through this skill, you will learn how the regression algorithm can be applied to fit a wide variety of relationships among data. You will also investigate if the effect of an independent variable depends on the level of another independent variable by including interaction terms in the multiple regression model. Another aspect of this skill is learning how to evaluate models, regression, or otherwise, to find the most favorable levels of the independent variables. In this skill, you’ll learn how to use the Solver Add-In to find the optimal level of inputs. You will also learn about the logit transformation that is used to convert a binary outcome to a linear relationship with the independent variables. Excel does not have a built-in logistic regression tool, so you will learn how to manually design a logistic regression model, and then optimize the parameters using the Solver Add-In tool.
Upon successful completion, you will be able to:
Apply the regression algorithm to fit a variety of relationships within the data
Use the Excel Solver Add-In tool to solve constrained maximization problems
Design a logistic regression model, and then optimize the parameters using the Excel Solver Add-In tool
Introduction Video
Introduction to the Skill
Glossary
Polynomial Regression Models
Categorical Variables
Multiple Indicator Variables
Interaction Terms
Regression Summary
Knowledge Check 1
Optimization with Excel Solver
Solver Constraints and Reports
Logit Transformation
Simple Logistic Regression
Logistic Regression Accuracy
Knowledge Check 2
Instructions and Materials
Exercise Part 1
Exercise Part 2
Debriefing
Conclusion Video
Final Quiz
Survey Instructions
Feedback Survey
Survey Verification
Next Steps