Taste Test: Likes vs. Comments


likes_vs_comments

This graph shows that as comment count increases, the number of like count increases, which demonstrates a positive relationship (r = 0.81).

The coefficient of determination, r2, is 0.65, indicating that 65% of the variation in comment count can be explained by like count. Further, knowing the comment count should allow us make an accurate estimate of like count.

To view the fit of the regression model to the data, the best-fitted line, "fitted line", has been plotted in red.

There appears to be a significant relationship between the number of comments and like count, as the p-value is <0.0001. The p-value shows the probability that the slope is zero, which indicates that there is no correlation between the two variables. In this case, the low p-value indicates that the probability that the two variables are not related are very low.

Collectively, these results demonstrate that there is a significant correlation between number of likes and comments for the BuzzFeed show, Taste Test.

Visualizations


BuzzFeed Unsolved

like_vs_comments

like_vs_views

BuzzFeed Taste Test

like_vs_views2

like_vs_views2