Linear Regression And Correlation: A Beginner's Guide

Linear Regression & Correlation

If you are looking for a short beginners guide packed with visual examples, this book is for you.

Linear Regression is a way of simplifying a group of data into a single equation.  For instance, we all know Moore’s law: that the number of transistors on a computer chip doubles every two years. This law was derived by using regression analysis to simplify the progress of dozens of computer manufacturers over the course of decades into a single equation.   Correlation is a way of calculating how much two sets of numbers change together.  In addition to being part of the regression analysis, correlation is heavily used in investment industries, for instance, to determine if two stocks are likely to change value together or independently.

This book goes through how to calculate correlation and linear regression and works through multiple examples of how to do it.  Just as importantly, this book is loaded with visual examples of what correlation is and how to use linear regression. This book doesn't assume that you have prior in-depth knowledge of statistics or that you regularly use an advanced statistics software package.  If you know what an average is and can use Excel, this book will build the rest of the knowledge, and do so in an intuitive way. 

This Is Not A Textbook

The reason I wrote this book is that there are not a lot of good examples out there of how to do multiple regression, which is regression analysis between more than two variables.  I checked half a dozen different sources, including several textbooks, on how to do multiple regression. In each case, the source had a lot of information; in some cases dozens of pages; on how to do the data preparation,  how to interpret results, and potential problems to watch out for, but to actually do the multiple regression calculation, they all said to use a software package, like Matlab or Minitab.

To put it a different way, those sources are a lot like a driver’s education class teaching you about setting the mirrors, adjusting the seat, and fastening the safety belt - but just when you think you are finally ready to actually start the car and put it in gear, they tell you to take the bus.

This book is different. It does not spend much time on the niceties of exactly how you should scrub your data, and instead just shows how to do the calculations, with examples.  This book is more like Grandpa showing you how to actually drive the old pickup truck from the farmhouse to the barn so you can get some work done.

What Is In This Book?

There are a number of examples shown in this book, they include

• How to do a correlation calculation
• An example of correlation on the stock price of 10 different big-name stocks, such as Coke and Pepsi
• How having uncorrelated investments can give you better returns at lower risk.
• How to do linear regression with two variables
• How to do multiple linear regression with any number of independent variables
• A regression analysis to predict the number of viewers in future episodes of the television show ‘Modern Family’
• How to evaluate the quality of your regression analysis using R-squared or adjusted R-squared
• How to do regression on exponential data, and recreate Moore’s law

If you are a visual learner and like to learn by example, this intuitive book might be a good fit for you. Regression and Correlation are fascinating topics. They are very important tools that are used in data analysis throughout a wide-range of industries - so take an easy dive into the topic with this visual approach!