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Read the following description of a data set.\newlineMr. Espinoza wants to demonstrate the importance of proofreading to his English class. He had students read the same passage and mark all the spelling and grammar errors they could find.He recorded how many minutes each student had spent on the exercise, xx, and how many errors that student had missed, yy.The least squares regression line of this data set is:y=1.332x+43.879y = -1.332x + 43.879\newlineComplete the following sentence:\newlineFor each additional minute a student spent proofreading, the least squares regression line predicts that he or she would miss __\_\_ fewer errors.

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Q. Read the following description of a data set.\newlineMr. Espinoza wants to demonstrate the importance of proofreading to his English class. He had students read the same passage and mark all the spelling and grammar errors they could find.He recorded how many minutes each student had spent on the exercise, xx, and how many errors that student had missed, yy.The least squares regression line of this data set is:y=1.332x+43.879y = -1.332x + 43.879\newlineComplete the following sentence:\newlineFor each additional minute a student spent proofreading, the least squares regression line predicts that he or she would miss __\_\_ fewer errors.
  1. Identify Slope: Identify the slope of the least squares regression line. The equation given is y=1.332x+43.879y = -1.332x + 43.879. The slope of the least squares regression line is the coefficient of xx, which is 1.332-1.332. This slope indicates the change in the number of errors missed (yy) for each additional minute spent proofreading (xx).
  2. Interpret Slope: Interpret the slope.\newlineSince the slope is 1.332-1.332, this means that for each additional minute a student spends proofreading, the number of errors they miss decreases by 1.3321.332. This is because the slope represents the change in the dependent variable (y)(y) for each one-unit increase in the independent variable (x)(x).

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