Asked by Harmanpreet Kaur Randhawa on May 27, 2024

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A regression analysis between weight (y in pounds) and height (x in inches) resulted in the following least squares line: A regression analysis between weight (y in pounds)  and height (x in inches)  resulted in the following least squares line:   = 128 + 6x. This implies that if the height is increased by 1 inch, the weight on average is expected to: A)  increase by 1 pound B)  decrease by 1 pound C)  increase by 6 pounds D)  decrease by 6 pounds E)  increase by 134 pounds = 128 + 6x. This implies that if the height is increased by 1 inch, the weight on average is expected to:

A) increase by 1 pound
B) decrease by 1 pound
C) increase by 6 pounds
D) decrease by 6 pounds
E) increase by 134 pounds

Least Squares Line

A line of best fit determined by minimizing the sum of the squares of the vertical distances of the points from the line.

Weight

A measure of the heaviness of an object; in statistics, it refers to the emphasis or importance assigned to elements of a dataset.

Height

The measurement of an object or point in relation to ground level or a base level, typically considered vertical distance.

  • Analyze the slope and intercept values in the context of regression line interpretation.
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ME
Madeline EllerbuschJun 03, 2024
Final Answer :
C
Explanation :
According to the least squares line, the coefficient for height is 6. This means that for every 1 inch increase in height, the weight is expected to increase by an average of 6 pounds. Therefore, the answer is choice C.