Introduction to complex data relationships-Get started with the course
Introduction to Course 5
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Helpful resources and tips
Tiffany: Gain actionable insights with regression models
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Course 5 overview
Welcome to module 1
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PACE in regression analysis
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Introduction to complex data relationships-Linear regression
Introduction to linear regression
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Mathematical linear regression
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Introduction to complex data relationships-Logistic regression
Introduction to logistic regression
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Introduction to complex data relationships-Review: Introduction to complex data relationships
Wrap-up
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Glossary terms from module 1
Simple linear regression-Foundations of linear regression
Welcome to module 2
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Jerrod: The incredible value of mentorship
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Ordinary least squares estimation
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Explore ordinary least squares
Correlation and the intuition behind simple linear regression
Simple linear regression-Assumptions and construction in Python
Make linear regression assumptions
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The four main assumptions of simple linear regression
Explore linear regression with Python
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Code functions and documentation
Simple linear regression-Evaluate a linear regression model
Evaluate uncertainty in regression analysis
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Interpret measures of uncertainty in regression
Model evaluation metrics
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Evaluation metrics for simple linear regression
Simple linear regression-Interpret linear regression results
Interpret and present linear regression results
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Correlation versus causation: Interpret regression results
Simple linear regression-Review: Simple linear regression
Wrap-up
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Glossary terms from module 2
Multiple linear regression-Understand multiple linear regression
Welcome to module 3
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Introduction to multiple regression
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Multiple linear regression scenarios
Multiple linear regression-Model assumptions revisited
Represent categorical variables
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Make assumptions with multiple linear regressions
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Multiple linear regression assumptions and multicollinearity
Multiple linear regression-Model interpretation
Interpret multiple regression coefficients
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Interpret multiple regression results with Python
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Multiple linear regression-Variable selection and model evaluation
The problem with overfitting
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Underfitting and overfitting
Top variable selection methods
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Regularization: Lasso, Ridge, and Elastic Net regression
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Multiple linear regression-Review: Multiple linear regression
Wrap-up
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Glossary terms from module 3
Advanced hypothesis testing-The chi-squared test
Welcome to module 4
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Hypothesis testing with chi-squared
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Chi-squared tests: Goodness of fit versus independence
Advanced hypothesis testing-Analysis of variance
Introduction to the analysis of variance
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More about ANOVA
Explore one-way vs. two-way ANOVA tests with Python
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ANOVA post hoc tests with Python
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Ignacio: Discovery at every stage of your career
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Advanced hypothesis testing-ANCOVA, MANOVA, and MANCOVA
ANCOVA: Analysis of covariance
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More dependent variables: MANOVA and MANCOVA
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Advanced hypothesis testing-Review: Advanced hypothesis testing
Wrap-up
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Glossary terms from module 4
Logistic regression-Foundations of logistic regression
Welcome to module 5
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Find the best logistic regression model for your data
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Logistic regression-Logistic regression with Python
Construct a logistic regression model with Python
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Logistic regression-Interpret logistic regression results
Evaluate a binomial logistic regression model
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Key metrics to assess logistic regression results
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Common logistic regression metrics in Python
Interpret the results of a logistic regression
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Interpret logistic regression models
Logistic regression-Compare regression models
Answer questions with regression models
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Prediction with different types of regression
Logistic regression-Review: Logistic regression
Wrap-up
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Glossary terms from module 5
Course 5 end-of-course project-Apply your skills to a workplace scenario
Welcome to module 6
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Leah: Strategies for sharing models and modeling techniques
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Introduction to your Course 5 end-of-course portfolio project
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Explore your Course 5 workplace scenarios
Course 5 end-of-course project-Automatidata scenario
Course 5 end-of-course portfolio project overview: Automatidata
Activity Exemplar: Create your Course 5 Automatidata project
Course 5 end-of-course project-TikTok scenario
Course 5 end-of-course portfolio project overview: TikTok
Activity Exemplar: Create your Course 5 TikTok project
Course 5 end-of-course project-Waze scenario
Course 5 end-of-course portfolio project overview: Waze
Activity Exemplar: Create your Course 5 Waze project
Course 5 end-of-course project-End-of-course portfolio project wrap-up
End-of-course project wrap-up and tips for ongoing career success
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Course 5 end-of-course project-Course review: Regression analysis: Simplifying complex data relationships
Reflect and connect with peers
Course 5 glossary
Course wrap-up
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Get started on the next course
Activity Exemplar_ Waze Course 5 executive summary-UHDWb5HdR9ekuN6wiKPMnw.pptx
(5.2 MB)
Activity Exemplar_ TikTok Course 5 executive summary-SoNiIBnBT0292i3a78di8w.pptx
(5.2 MB)
Activity Exemplar_ Course 5 Automatidata Executive Summary-X_D0gtxZSS6pcdbZxMCw_w.pptx
(5.1 MB)
