College of St Joseph Linear Model Appropriate and Regression Line Problems

here is the question which you don’t have to write.

Choose EITHER Option A or Option B for your initial post.

Option A:
An SRS of apartment listings in a large northeastern city comparing monthly rent ($) versus size (〖ft〗^2) yields following computer output: check attached picture

1. Is a linear model appropriate for these data?Explain
2. Interpret the slope of the regression line.〖^〗
3. interpret r^2 in context.
4. B:The calories and sugar content per serving size of ten brands of breakfast cereal are fitted with a least squares regression line with computer outputs: check attached picture.
5. Is a linear model appropriate for these data?Explain
6. Interpret the slope of the regression line.〖^〗
7. Interpret r^2 in context.

8. Now this is the reply from others. All you have to give them proper feedback about their writing.

   A. In regard to the Discussion Board this week, I hereby choose Option A:1.) Despite the fluctuations in the residuals graph, the monthly rent vs. size linear model is, indeed, appropriate. This is because that the line of regression has a positive correlation between monthly rent and size. In other words, an increase in apartment size will generally result in an increase in monthly rent.2.) Based on the best interpretation of the data given, the slope of the regression line is approximately “b = 1.03.”3.) In context, the coefficient of determination (r^2) is approximately “0.956” or more appropriately “95.6%.” Therefore, the linear model explains an overwhelming majority of the variability of the response data around its mean. In other words, the linear model fits the data quite excellently as a result of the value of r^2 being such a high percentage. B. Option B:
   The calories and sugar content per serving size of ten brands of breakfast cereal are fitted with a least squares regression line with computer outputs:
   1. Is a linear model appropriate for these data?Explaina. I would say that a linear model would be appropriate since the data presented shows a good correlation between sugar and calories in these cereal brands.2. Interpret the slope of the regression line.〖^〗a. With a slope of 2.74239 it stands to reason that the as the sugar increases in a cereal that the calories will increase as well.3. Interpret r^2 in context.a. With r2 being 77.9% it shows that the coefficient of determination shows a good correlation between the increase in sugar in a cereal will also increase the calories in that cereal per serving.