4. Set up a regression model using the specific variable names, betas, and an error term.

- Y is Transactions

- Xs are Impressions, Reach, Likes, Post_Hour, Photo, Product_Info, and Paid_Ad

5. Write down the estimated equation after running the regression model.

Descriptives [DataSet1] /Users/bransonknowles/Downloads/b. Download Files Assignment Descriptive Statistics Minimum Maximum N Mean Std. Deviation 500 9 1415.13 2000.594 500 570 238 Transactions Impressions Reach Likes Post_Hour Valid N (listwise) 500 500 19779 1110282 180480 4376 23 29585.95 13903.36 609.99 76803.247 22740.788 612.726 4.369 9 500 1 7.84 500 Frequencies Statistics Photo Product_Info 500 500 Paid_Ad 500 N Valid Missing 0 0 0 Frequency Table Photo Cumulative Percent Percent Valid Percent Frequency 74 Valid 0 14.8 14.8 14.8 1 426 85.2 85.2 100.0 Total 500 100.0 100.0 Product_Info Cumulative Percent Percent Valid Percent Frequency 370 Valid 0 74.0 74.0 1 130 26.0 74.0 26.0 100.0 100.0 Total 500 100.0 Paid_Ad Cumulative Percent Percent Valid Percent Frequency 361 Valid 0 72.2 72.2 72.2 100.0 1 139 27.8 27.8 Total 500 100.0 100.0 Descriptives [DataSet1] /Users/bransonknowles/Downloads/b. Download Files Assignment Descriptive Statistics Minimum Maximum N Mean Std. Deviation 500 9 1415.13 2000.594 500 570 238 Transactions Impressions Reach Likes Post_Hour Valid N (listwise) 500 500 19779 1110282 180480 4376 23 29585.95 13903.36 609.99 76803.247 22740.788 612.726 4.369 9 500 1 7.84 500 Frequencies Statistics Photo Product_Info 500 500 Paid_Ad 500 N Valid Missing 0 0 0 Frequency Table Photo Cumulative Percent Percent Valid Percent Frequency 74 Valid 0 14.8 14.8 14.8 1 426 85.2 85.2 100.0 Total 500 100.0 100.0 Product_Info Cumulative Percent Percent Valid Percent Frequency 370 Valid 0 74.0 74.0 1 130 26.0 74.0 26.0 100.0 100.0 Total 500 100.0 Paid_Ad Cumulative Percent Percent Valid Percent Frequency 361 Valid 0 72.2 72.2 72.2 100.0 1 139 27.8 27.8 Total 500 100.0 100.0