and the high school graduation rate, x. The linear regression equation for predicting poverty is as follows:         y=64.68−0.62x   The actual high school graduation rate for a certain state is 93.3%, and the actual poverty rate in that state is 4.734%. What is the residual for this observation?

The sweetness, y, of the fruit is supposed to be related to the average daily sunshine hours, x. The following data shows the sweetness of the same type of fruit at different locations (sunshine hours). Fit the data to a simple linear regression model. x: 5, 6, 7, 6, 6, 8, 7, 5. y: 9, 10, 10, 11, 12, 13, 12, 8. Predict the true mean sweetness for average daily hours of 8 hours, and calculate the residual for average daily sunshine hours of 8 hours.

A graphing calculator is recommended. When laboratory rats are exposed to asbestos fibers, some of them develop lung tumors. The table lists the results of several experiments by different scientists. Asbestos exposure (fibers/mL) y = 50 Mice with Tumors (%) 400 O 500 900 1,100 1,600 1,800 2,000 3,000 3000 2500 2000 1500 (a) Find the regression line for the data. (Use x for asbestos exposure in fibers/mL and y for percent of mice with tumors. Round your values to four decimal places.) 1000 500 Percent of mice that develop lung tumors (b) Construct a scatter plot and graph the regression line. o 0 7 6 11 10 27 41 38 37 49 20 30 40 50 Asbestos Exposure (Fibers/mL.) 60 Mice with Tumors (%) 3000 ● 2500 2000 1500 1000 500 60 0 0 10 20 30 40 50 60 Asbestos Exposure (Fibers/mL) Ⓡ 4

If a correlation isr= 0.00, then SP = 0 and the regression equation is O Ý =X +0 O Ý =X + X O Ý =0 + X O Ý =Ÿ + 0