Section 6.3 Conclusion
Subsection 6.3.1 Additional resources
An R script file of all R code used in this chapter is available here.
Subsection 6.3.2 What’s to come?
This chapter concludes the “Statistical/Data Modeling with
moderndive” portion of this book. We are ready to proceed to Part III: “Statistical Inference with infer.” Statistical inference is the science of inferring about some unknown quantity using sampling. So far, we have only studied the regression coefficients and their interpretation. In later chapters we learn how we can use information from a sample to make inferences about the entire population.
Once we have covered Chapter 7 on sampling, Chapter 8 on confidence intervals, and Chapter 9 on hypothesis testing, we revisit the regression models in Chapter 10 on inference for regression. This will complete the topics in this book, as shown in Figure 6.3.1!
Also in Chapter 10, we revisit the concept of residuals \(y - \widehat{y}\) and discuss their importance when interpreting the results of a regression model. We perform what is known as a residual analysis of the
residual variable of all get_regression_points() outputs. Residual analyses enable us to verify what are known as the conditions for inference for regression.
