# applied statistics and optimization

## Project Description:

1. determine the equation of the regression line.

x 12 21 28 8 20
y 17 15 22 19 24

2. determine the equation of the regression line for the following data, and compute the residuals.

x 16 9 20 13 5
y 47 39 56 45 22

3.solve for the predicted values of y and the residuals for the following data.
business bankruptcies (1000) firm births (10,000)
34.3 58.1
35.0 55.4
38.5 57.0
40.1 58.5
35.5 57.4
37.9 58.0

4.wisconsin is an important milk-producing state. some people might argue that because of transportation costs, the cost of milk increases with the distance of markets from wisconsin. suppose the milk prices in eight cities are as follows.

cost of milk
(per gallon) distance from madison(miles)
\$2.64 1,245
2.31 425
2.45 1,346
2.52 973
2.19 255
2.55 865
2.40 1,080
2.37 296

a. use the prices along with the distance of each city from madison,wisconsin, to develop a regression line to predict the price of a gallon of milk by the number of miles the city is from madison. also find the residuals using the data and regression equation.
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Price Type: Fixed

Project Budget: \$10 to \$20
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