A company wishes to determine the relationship between the number of days spent

Question

A company wishes to determine the relationship between the number of days spent training employees and their performances on a job aptitude test. Collected data result in a least squares regression line, y = 12.1 + 6.2 x, where x is the number of training days and y is the predicted score on the aptitude test. Which of the following statements best interprets the slope and y-intercept of the regression line? (A) The base score on the test is 12.1, and for every day of training one would expect, on average, an increase of 6.2 on the aptitude test. (B) The base score on the test is 6.2, and for every day of training one would expect, on average, an increase of 12.1 on the aptitude test. (C) The mean number of training days is 12.1, and for every additional 6.2 days of training one would expect, on average, an increase of one unit on the aptitude test. (D) The mean number of training days is 6.2, and for every additional 12.1 days of training one would expect, on average, an increase of one unit on the aptitude test. (E) The mean number of training days is 12.1, and for every day of training one would expect, on average, an increase of 6.2 on the aptitude test.

Explanation / Answer

Here slope is: 6.2

It shows that for each unit increase in x (number of training days), the dependent variable y is increased by 6.2 units.

The intercept is : 12.1

When number of trianing days is zero then apptitude score is 12.1.

Option A is correct.

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