Correlation and Regression

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Correlation and Regression

Presentation transcript:

Correlation and Regression CHAPTER nine Correlation and Regression

Section 9.1 Correlation

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

Types of correlation:

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.

Section 9.2 Linear regression

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…

Finding m and b

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