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1d.  Give the adjusted R-squared for this model. (Round final answers to 4 decimal places) Adjusted R-Squared: 2. You will now obtain regression estimates predicting Attendance from the number of Flyers posted around town, whether the flyers were posted in Color, and the interaction between Flyers and Color.  Again, assume standard regression assumptions hold.  As a quick double-check of your work, you should find that the adjusted R-squared for this model is 0.9219. 2a.  Give the regression estimate assuming the model:  Attendance = β0 + β1*Flyers + β2*Color+β3*(Flyers*Color). (Round your answers to 4 decimal places.) Attendance =    +.    * (Flyers)  +  *(Color) +   *(Flyers*Color)   2b.  How many people are expected to attend if the band posted 80 flyers printed in color around town under this interaction model?  (Round final answers to 2 decimal places.) Predicted Attendance:

1d.  Give the adjusted R-squared for this model. (Round final answers to 4 decimal places) Adjusted R-Squared: 2. You will now obtain regression estimates predicting Attendance from the number of Flyers posted around town, whether the flyers were posted in Color, and the interaction between Flyers and Color.  Again, assume standard regression assumptions hold.  As a quick double-check of your work, you should find that the adjusted R-squared for this model is 0.9219. 2a.  Give the regression estimate assuming the model:  Attendance = β0 + β1*Flyers + β2*Color+β3*(Flyers*Color). (Round your answers to 4 decimal places.) Attendance =    +.    * (Flyers)  +  *(Color) +   *(Flyers*Color)   2b.  How many people are expected to attend if the band posted 80 flyers printed in color around town under this interaction model?  (Round final answers to 2 decimal places.) Predicted Attendance:

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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1d.  Give the adjusted R-squared for this model. (Round final answers to 4 decimal places)

Adjusted R-Squared:

2. You will now obtain regression estimates predicting Attendance from the number of Flyers posted around town, whether the flyers were posted in Color, and the interaction between Flyers and Color.  Again, assume standard regression assumptions hold.  As a quick double-check of your work, you should find that the adjusted R-squared for this model is 0.9219.

2a.  Give the regression estimate assuming the model:  Attendance = β0 + β1*Flyers + β2*Color+β3*(Flyers*Color). (Round your answers to 4 decimal places.)

Attendance =    +.    * (Flyers)  +  *(Color) +   *(Flyers*Color)

 

2b.  How many people are expected to attend if the band posted 80 flyers printed in color around town under this interaction model?  (Round final answers to 2 decimal places.)

Predicted Attendance:

A local band hires a statistician to determine whether flyers are effective for increasing the audience for shows. For the band's last eight shows, the statistician records how many people attended the shows (Audience), how many flyers were posted around town (Flyers), and whether or not the flyers were printed in color (Color = 1 if the flyers were printed in color, Color = 0 otherwise). The complete data is contained in the accompanying table. Attendance 261 460 390 268 200 249 449 275 Flyers 70 80 70 40 30 90 70 70 Color O 1 1 1 O 1 1. You will obtain regression estimates predicting Attendance from the number of Flyers posted around town and whether the flyers were posted in Color. Assume standard regression assumptions hold.
Transcribed Image Text:A local band hires a statistician to determine whether flyers are effective for increasing the audience for shows. For the band's last eight shows, the statistician records how many people attended the shows (Audience), how many flyers were posted around town (Flyers), and whether or not the flyers were printed in color (Color = 1 if the flyers were printed in color, Color = 0 otherwise). The complete data is contained in the accompanying table. Attendance 261 460 390 268 200 249 449 275 Flyers 70 80 70 40 30 90 70 70 Color O 1 1 1 O 1 1. You will obtain regression estimates predicting Attendance from the number of Flyers posted around town and whether the flyers were posted in Color. Assume standard regression assumptions hold.
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