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Regression Analysis: Simplify Complex Data Relationships

Google via Google Skills

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Overview

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This is the fourth course in the Google Advanced Data Analytics Certificate. Data professionals use regression analysis to discover the relationships between different variables in a dataset and identify key factors that affect business performance. In this course, you’ll practice modeling variable relationships. You'll learn about different methods of data modeling and how to use them to approach business problems. You’ll also explore methods such as linear regression, analysis of variance (ANOVA), and logistic regression. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete the eight courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate.

Syllabus

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

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