# Regression Analysis using R and SAS

*2019-09-27*

# Chapter 1 Prerequisites

Before we talk about regression theory, we need to review some basic statistical inference methods and matrix algebra.

This book referred from many books including rowlings’ “Applied Regression Analysis: A research Tool”. \(\beta=(\mathbf{X'X})^{-1}\mathbf{X'y}\).

A *matrix* is a square shape array of numbers (sometimes can be string). In this book, boldface letters mean matrices. For example,
\[
\mathbf{A}=
\begin{pmatrix}
65 & 154 \\
73 & 182 \\
68 &167
\end{pmatrix}.
\]

This is a *sample* book written in **Markdown**. You can use anything that Pandoc’s Markdown supports, e.g., a math equation \(a^2 + b^2 = c^2\).

The **bookdown** package can be installed from CRAN or Github:

```
install.packages("bookdown")
# or the development version
# devtools::install_github("rstudio/bookdown")
```

Remember each Rmd file contains one and only one chapter, and a chapter is defined by the first-level heading `#`

.

To compile this example to PDF, you need XeLaTeX. You are recommended to install TinyTeX (which includes XeLaTeX): https://yihui.name/tinytex/.