Bytelearn - cat image with glassesAI tutor

Welcome to Bytelearn!

Let’s check out your problem:

Read the following description of a data set.\newlineFulton County's Parks and Recreation Department is considering establishing a new park. As part of the decision-making process, the department asked an intern to conduct a park usage study.The study considered the area (in square kilometers), xx, and the number of visitors last year, yy, of each county park.The least squares regression line of this data set is:y=10,637.929x+134,391.457y = 10,637.929x + 134,391.457\newlineComplete the following sentence:\newlineIf a park's area was one square kilometer larger, the least squares regression line predicts that it would have had __\_\_ more visitors last year.

Full solution

Q. Read the following description of a data set.\newlineFulton County's Parks and Recreation Department is considering establishing a new park. As part of the decision-making process, the department asked an intern to conduct a park usage study.The study considered the area (in square kilometers), xx, and the number of visitors last year, yy, of each county park.The least squares regression line of this data set is:y=10,637.929x+134,391.457y = 10,637.929x + 134,391.457\newlineComplete the following sentence:\newlineIf a park's area was one square kilometer larger, the least squares regression line predicts that it would have had __\_\_ more visitors last year.
  1. Identify Slope: Identify the slope of the least squares regression line. The equation given is y=10,637.929x+134,391.457y = 10,637.929x + 134,391.457. The slope of the least squares regression line is the coefficient of xx, which is 10,637.92910,637.929. This slope indicates the change in the number of visitors for each one square kilometer increase in park area.
  2. Interpret Slope: Interpret the slope in the context of the problem.\newlineSince the slope is 10,637.92910,637.929, this means that for each additional square kilometer of park area, the number of visitors is predicted to increase by 10,637.92910,637.929.

More problems from Interpret regression lines