a. Estimate a typical, ordinary least squares regression model which explains how many (in thousands) clicks a social media video will receive as a function of two predictors: both the channel (X or Y) that hosts the video and the number of paid social media promoters devoted to sharing the video. Write out this estimated equation to explain how many clicks are received (use the estimate values and the specific predictors (not 'x1' e.g.)!).

b. Provide the residual plots against each of the two explanatory variables you used in "a" above (channel and promoter). Comment on any irregularities that you notice. If you notice any irregularities in part "b", above, attempt other models which utilize quadratic and/or interaction terms with thickness and manufacturer remaining as explanatory variables.

c. If you find a model with residuals better in line with the regression assumptions, then write out this new, estimated model. Comment on the statistical significance levels of the predictors and provide and comment on the new residual plots for your finalized model.

Video Clicks (in thousands)	Host	Promoters
9	X	1
49	X	5
225	X	5
1089	X	8
1600	X	10
4225	X	12
4489	X	13
7225	X	15
9801	X	17
16900	X	20
19321	X	21
25600	X	23
49	Y	2
64	Y	4
144	Y	4
484	Y	7
2916	Y	12
4624	Y	13
6084	Y	15
7569	Y	16
10000	Y	18
14400	Y	20
17689	Y	21
19600	Y	22