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Chapter 7
Simple Linear Regression
“All models are wrong, but some are useful.”
— George E. P. Box
After reading this chapter you will be able to:
• Understand the concept of a model.
• Describe two ways in which regression coefficients are derived.
• Estimate and visualize a regression model using R.
• Interpret regression coefficients and statistics in the context of real-world
problems.
• Use a regression model to make predictions.
7.1 Modeling
Let’s consider a simple example of how the speed of a car affects its stopping
distance, that is, how far it travels before it comes to a stop. To examine this
relationship, we will use the cars dataset which, is a default R dataset. Thus,
we don’t need to load a package first; it is immediately available.
To get a first look at the data you can use the View() function inside RStudio.
View(cars)
We could also take a look at the variable names, the dimension of the data
frame, and some sample observations with str().
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