EBK ESSENTIAL STATISTICS FOR THE BEHAVI
2nd Edition
ISBN: 8220107093466
Author: PRIVITERA
Publisher: SAGE
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Chapter 13, Problem 22CAP
To determine
To find: The best fit regression line for the provided data set.
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A regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The least squares regression line is weight = -5.94 + 0.1875 length.
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An engineer wants to determine how the weight of a gas-powered car, x, affects gas mileage, y. The accompanying data represent the weights of various domestic cars and their miles per gallon in the city for the most recent model year. Complete parts (a)
Find the least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable.
Suppose the manager of a gas station monitors how many bags of ice he sells daily along with recording the highest temperature each day during the summer. The data are plotted with temperature, in degrees Fahrenheit (°F), as the explanatory variable and the number of ice bags sold that day as the response variable. The least squares regression (LSR) line for the data is ?ˆ=−151.05+2.65?Y^=−151.05+2.65X.
On one of the observed days, the temperature was 82 °F82 °F and 68 bags of ice were sold. Determine the number of bags of ice predicted to be sold by the LSR line, ?ˆY^, when the temperature is 82 °F.82 °F. Enter your answer as a whole number, rounding if necessary.
Chapter 13 Solutions
EBK ESSENTIAL STATISTICS FOR THE BEHAVI
Ch. 13 - Prob. 1FPCh. 13 - Prob. 2FPCh. 13 - Prob. 3FPCh. 13 - Prob. 4FPCh. 13 - Prob. 5FPCh. 13 - Prob. 6FPCh. 13 - Prob. 7FPCh. 13 - Prob. 8FPCh. 13 - Prob. 9FPCh. 13 - Prob. 10FP
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