The spreadsheet below contains data about the current and lagged variables from the pop-culture blogger's tweets and the number of followers she gained that week. Create a regression model to predict the number of followers from the current week, the previous week, and the two weeks prior. Be sure to include the residuals and residual plots in your analysis.

Recall that each lagged variable creates an incomplete line of data. You cannot include blank cells in your regression cell ranges and the labels are no longer contiguous with the data of interest. Thus, you should only select rows with complete data and leave theLabelsbox unchecked.

Note that leaving theLabelsbox unchecked is unique to this data setup (when the lagged data has created blank cells between the number values and the column labels). Generally, you would always want to use labels in a regression.

A B C D E Week starting New followers Weekly tweets Tweets from Tweets from two previous week weeks prior January 3, 2016 10 January 10, 2016 12 NJ January 17, 2016 7 W January 24, 2016 5 5 January 31, 2016 10 February 7, 2016 12 O un W n CO UI N O O U W N N February 14, 2016 15 February 21, 2016 18 5 6 February 28, 2016 14 8 March 6, 2016 21 15 March 13, 2016 31 11 15 March 20, 2016 28 10 11 15 March 27, 2016 15 11 10 11 April 3, 2016 20 15 11 10 April 10, 2016 18 17 15 11 April 17, 2016 27 20 17 15 April 24, 2016 35 21 20 17 21 20 21