October 2023
Beginner
516 pages
12h 12m
English
Content preview from The Statistics and Machine Learning with R Workshop
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12
Linear Regression in R
In this chapter, we will introduce linear regression, a fundamental statistical approach that’s used to model the relationship between a target variable and multiple explanatory (also called independent) variables. We will cover the basics of linear regression, starting with simple linear regression and then extending the concepts to multiple linear regression. We will learn how to estimate the model coefficients, evaluate the goodness of fit, and test the significance of the coefficients using hypothesis testing. Additionally, we will discuss the assumptions underlying linear regression and explore techniques to address potential issues, such as nonlinearity, interaction effect, multicollinearity, and heteroskedasticity. ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.