I am getting stuck on the below question and I'm unsure if its because I'm getting the answer wrong or if its a system error so I would appreciate a very specific clear step by step response so I can compare your process to my own to ensure I can determine where the fault lies. thank you.

Question to be answered -

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. I need 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.

Regression INPUT- Input Y Range: Input X Range: Grouped By: OColumns ORows Labels Constant is Zero Confidence Level 95 OUTPUT- OOutput Range G1 New Worksheet Ply New Worksheet RESIDUALS Residuals O Residual Plots Standardized Residuals OLine Fit Plots NORMAL PROBABILITY Normal Probability Plots OKHOME INSERT DATA fx Week starting A B C D E Week starting New followers Weekly tweets Tweets from Tweets from two previous week weeks prior = 2 January 3, 2016 10 3 January 10, 2016 12 4 January 17, 2016 7 5 January 24, 2016 5 6 January 31, 2016 10 7 February 7, 2016 12 8 February 14, 2016 15 9 February 21, 2016 18 10 February 28, 2016 14 8 11 March 6, 2016 21 15 12 March 13, 2016 31 11 13 March 20, 2016 28 10 14 March 27, 2016 15 11 10 11 15 April 3, 2016 20 15 10 16 April 10, 2016 18 17 15 11 17 April 17, 2016 27 20 17 15 18 April 24, 2016 35 21 20 17 19 21 20 20 21 21 22 23 24 25If your regression is hanging up on the processing OR if the submit button is not enabled, you will need to click "Reset" and try again. There are two common errors with this spreadsheet exercise: not including enough independent (or x) variables and/or not including the correct rows of data. Including Enough Independent Variables You can use the second spreadsheet question on this page (where you set up the regression with the Previous Year's Advertising lagged variable) as a model for completing this question. Here, however, we have two columns of lagged independent variables instead of just one, so our x-range will span three columns instead of just two. Also, the number of rows that we can use will be reduced. If you have chosen the correct number of independent variables, there should be three residual plots generated. If you don't have three plots, you will need to click "Reset" and start over. Including the Correct Number of Rows Recall that we can only use complete rows of data in a regression. Blank cells will cause the regression process to hang. Therefore, look over the data and note which rows have a numeric value in each of these columns: B, C, D, and E. Use only those complete rows for your ranges. The correct data range will essentially be a block of complete rows with incomplete rows above and below. If you have three residual plots but still can't submit, make sure that you have included all of the valid rows. This is one of the few regression questions in the course where we specifically ask you to not use labels. Do not attempt to include the label cells and do not check off the "Labels" box in the setup. If issues persist, click "Reset" and start over, being sure to take a screen shot of your regression setup before running the regression again. If you're still not able to submit, send the screen shot of the full regression setup (not the error or the output) to hbsonlinesupport@hbs.edu