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A cost analyst was hired by a group of livestock auction market managers to determine how the number of various classes of livestock (cattle, calves, hogs, and sheep) sold at their markets influenced the cost of operations of their markets. Data was provided by 19 market managers.

Find the multiple linear regression function for expressing cost of operations as a function of the number of livestock sold for the four classes.

SAS Institute Inc.

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The Auction data set contains data from 19 livestock auction markets, including the number of head of each of four types of livestock sold (in thousands), the cost of operation of the auction market (in thousands of dollars), and the market identifier.

These are the variables in the data set:

This data is sample data from SAS Institute Inc.

Based on the parameter estimates, the multiple linear regression function is given by

Y-hat = 2.28842 + 3.21552X1 + 1.61315X2 + 0.81485X3 + 0.80258X4,

where Y-hat is the predicted cost of operations (in thousands of dollars) and X1 is the number of cattle sold, X2 is the number of calves sold, X3 is the number of hogs sold, and X4 is the number of sheep sold (in thousands).