1. Correlation and Regression
CHAPTER nine
Correlation and Regression

2. Section 9.1
Correlation

3. Definitions Correlation is a relationship between 2 variables.
Data is often represented by ordered pairs (x, y) and graphed on a scatter plot
X is the independent variable
Y is the dependent variable

4. Types of correlation:

5. CORRELATION COEFFICIENT
A numerical measure of the strength and direction of a linear relationship between 2 variables x and y.
-1 < r < 1 The closer to -1 or 1, the stronger the linear correlation. The closer to 0, the weaker the linear correlation.

7. Section 9.2
Linear regression

8. Regression Line
The line whose equation best fits the data in a scatter plot. We can use the equation to predict the value y for a given value of x. Recall: basic form of a line is y = mx + b We’ll use this form, but calculate m and b differently…

9. Finding m and b

10. Find the equation of the regression line
18. The square footages and sale prices (in thousands of dollars) of seven homes.
Use the line of regression to predict the sale price of a home when x = 1450 sq feet.
Sq Ft, x
1924
1592
2413
2332
1552
1312
1278
Sale Price, y
174.9
136.9
275.0
219.9
120.0
99.9
145.0