1. LEARNING GOALS FOR LESSON 2.7
Fit scatter plot data using linear models with technology.
Use linear models to make predictions.
Scatter plot:
Their main purpose is to analyze a relationship between 2 variables.:
Form
Direction
Strength:
Regression line or line of best fit: •
Try to have about the same number of points above and below the line of best fit.
Helpful Hint • • • • • • • • •

2. The correlation coefficient r is a measure of how strongly the data set is fit by a model.
Find the regression line and the correlation coefficient using the data below.

3. Example 2 Using Technology to Model Linear Data
LG 2.7.1
The gas mileage for randomly selected cars based upon engine horsepower is given in the table.
a. Make a scatter plot of the data with horsepower as the independent variable.
To graph a scatter plot on your calculator; press 2nd, Y=, 1:Plot1…On,
Make sure that On is highlighted, that the scatterplot is highlighted, that the Xlist says L1 and the Ylist says L2.
Hit ZOOM 9:ZoomStat
b. Find the correlation coefficient r and the line of best fit. Interpret the slope of the line of best fit in the context of the problem.

4. Example 3: Anthropology Application
LG 2.7.1
Anthropologists can use the femur, or thighbone, to estimate the height of a human being. The table shows the results of a randomly selected sample.
a. Make a scatter plot of the data with femur length as the independent variable.
b. Find the correlation coefficient r and the line of best fit. Interpret the slope of the line of best fit in the context of the problem.
LG 2.7.2
c. Use the Linear Regression equation you found to answer the question by plugging in.
A man’s femur is 41 cm long. Predict the man’s height.