Regression Analysis: Simplify Complex Data Relationships

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Overview

This is the fifth of seven courses 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, youll practice modeling variable relationships. You'll learn about different methods of data modeling and how to use them to approach business problems. Youll also explore methods such as linear regression, analysis of variance (ANOVA), and logistic regression. Google employees who...

Syllabus

Introduction to complex data relationships

Youll begin by exploring the main steps for building regression models, from identifying your assumptions to interpreting your results. Next, youll explore the two main types of regression: linear and logistic. Youll learn how data professionals use linear and logistic regression to approach different kinds of business problems.

Simple linear regression

Youll explore how to use models to describe complex data relationships. Youll focus on relationships of correlation. Then, youll build a simple linear regression model in Python and interpret your results.

Multiple linear regression

After simple regression, youll move on to a more complex regression model: multiple linear regression. Youll consider how multiple regression builds on simple linear regression at every step of the modeling process. Youll also get a preview of some key topics in machine learning: selection, overfitting, and the bias-variance tradeoff.

Advanced hypothesis testing

Youll build on your prior knowledge of hypothesis testing to explore two more statistical tests: Chi-squared and analysis of variance (ANOVA). Youll learn how data professionals use these tests to analyze different types of data. Finally, youll conduct two kinds of Chi-squared tests, as well as one-way and two-way ANOVA tests.

Logistic regression

Youll investigate binomial logistic regression, a type of regression analysis that classifies data into two categories. Youll learn how to build a binomial logistic regression model and how data professionals use this type of model to gain insights from their data.