# Chapter 11: Linear Regression and Chi-Squared

**At Grade**Created by: CK-12

In this chapter, you will learn how to use observed data to predict the value of an observation that you do not have. One way to do this is via ** linear regression**, the process of calculating a line that represents the best average rate of change of points in a scatter plot.

You will learn to evaluate a set of data to see if it supports a hypothesized distribution, and you will also learn to create contingency tables to organize information to compare variables and see if they are related. The chi-squared \begin{align*}(\chi^2)\end{align*} statistic is a value you will learn to use for this purpose.

- 11.1.
## Linear Relationships

- 11.2.
## Linear Correlation Coefficient

- 11.3.
## Least Squares

- 11.4.
## Contingency Tables

- 11.5.
## Chi Squared Statistic

- 11.6.
## Chi-Squared II – Testing for Independence

### Chapter Summary

Students were introduced to the concept of linear regression and Pearson’s correlation coefficient. Students learned to calculate a line of best fit using the least squares method.

After a review of the creation of contingency tables, students practiced extracting data from them to calculate the Chi-Squared statistic. Finally the students learned to use chi-square statistic to run chi-square tests of goodness of fit and variable independence.