We analyzed the relationship between IMDb ratings and Rotten Tomato ratings for 75 popular movies. The scatterplot showed a fairly strong, positive linear association. StatCrunch linear regression results are shown below. Simple linear regression results: Dependent Variable: Rotten_Tomatoes Independent Variable: IMDb_Rating Rotten_Tomatoes = -57.599288 + 17.919209 IMDb_Rating Sample size: 75 R (correlation coefficient) = 0.79786226 R-sq = 0.63658418 Estimate of error standard deviation: 12.916488 Which number describes the percentage of variability in Rotten Tomato ratings that is explained by the changes in IMDb ratings as described by the regression line? Group of answer choices: a) 0.80 b) 0.64 c) 17.9 d) 12.9
Added by Danielle H.
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In this case, the R-squared value is 0.63658418, which means that approximately 63.66% of the variability in Rotten Tomato ratings can be explained by the changes in IMDb ratings according to the regression line. Show more…
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We analyzed the relationship between the budgets (in millions of dollars) and the U.S. Box Office Sales (in millions of dollars) for 75 popular movies. The scatterplot showed a weak positive association with a linear form. Here are the StatCrunch linear regression results: Simple linear regression results: Dependent Variable: US_Box_Office Independent Variable: Budget US_Box_Office = -57.599288 + 17.919209 * IMDb_Rating Sample size: 75 R (correlation coefficient) = 0.79786226 R-sq = 0.63658418 Estimate of error standard deviation: 12.916488 Which number describes the percentage of variability in Rotten Tomato ratings that is explained by the changes in IMDb ratings as described by the regression line? This is the slope of the regression line. It describes the predicted change in Rotten Tomato ratings when IMDb ratings increase by one. a. 0.80 b. 0.64 c. 12.9 d. 17.9
Christine Y.
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