56...60: The same features as the attributes 51...55, but features 56...60 refer to the number Of links (trackbacks), while features 51...55 refer to the number of comments. 61: The length of time between the publication of the blog post and basetime 62: The length of the blog post 63...262: The 200 bag of words features for 200 frequent words of the text of the blog post 263...269: binary indicator features (0 or 1) for the weekday (Monday...Sunday) of the basetime 270...276: binary indicator features (0 or 1) for the weekday (Monday...Sunday) of the date of publication of the blog post 277: Number of parent pages: we consider a blog post P as a parent of blog post B, if B is a reply (trackback) to blog post P. 278...280: Minimum, maximum, average number of comments that the parents received 281: The target: the number of comments in the next 24 hours (relative to basetime) Questions Using the dataset above, perform a regression analysis, and comment on your results. 1) Do your best to create your final model and show all your steps (e.g., how to select your variables) 2) Suggest your final model as an equation. (based on Adjusted R-Square) 3) Include at least one interaction term into your final model 4) Discuss the interpretations in plain English and various output statistics (i.e., interpret the coefficient of each independent variable, significance of each independent variable, which independent variables are important? etc). 5) Provide all your processes in a word file including results, interpretation, and your comments, R-codes, etc