Book Image

Introduction to R for Business Intelligence

By : Jay Gendron
Book Image

Introduction to R for Business Intelligence

By: Jay Gendron

Overview of this book

Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.
Table of Contents (19 chapters)
Introduction to R for Business Intelligence
About the Author
About the Reviewers
R Packages Used in the Book
R Code for Supporting Market Segment Business Case Calculations

Chapter 4.  Linear Regression for Business

Linear regression is a powerful tool that enables the business analyst to perform data analytics and business intelligence. Linear regression is a statistical technique to represent relationships between two or more variables using a linear equation. You can use linear regression to predict an outcome, given some input. This chapter covers five topics that will give you the skills to use this technique in your analyses:

  • Understanding linear regression

  • Checking model assumptions

  • Using a simple linear regression

  • Refining data for simple linear regression

  • Introducing multiple linear regression

Together, these topics provide a building-block approach to not only teach you the skills to build linear models, but also shape your analytical thinking. Using this approach with other datasets will help you to keep practicing these skills.


Use case: The Marketing Dataset

The marketing manager has asked you to analyze marketing data to provide insights about...