Homework 3 – Regression Analysis

Regression Analysis代写 The dataset for this exercise is available in VideoGamesSales_Main.7bdat. This dataset contains information on the global sales

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The dataset for this exercise is available in VideoGamesSales_Main.7bdat. This dataset contains information on the global sales and critic and user review ratings for videogames launched between 2001 and 2012 (from www.vgchartz.com).Regression Analysis代写

The variables are: Regression Analysis代写

  • Name of the game
  • Videogame platform on which it was released.
Platform  
DS Nintendo DS
GBA Nintendo Game Boy Advance
GC Nintendo Game Cube
PC Personal Computer
PS2 Sony PlayStation 2
PS3 Sony PlayStation 2
PSP Sony PlayStation Portable
Wii Nintendo Wii
X360 Microsoft XBOX 360
XB Microsoft XBOX

 

 

 

 

 

 

 

 

 

       Regression Analysis代写

  • Videogame Genre (e.g., Action, Sports, Shooter etc.)
  • Publisher
  • Developer
  • Rating: E = Everyone, E10+ = Everyone 10+, T = Teen, M = Mature
  • Global Sales (Millions of units)
  • Year of release
  • Critic Score (0 – 100): Average critic rating
  • Critic Count : Number of critic ratings
  • User Score  (0 – 10): Average user rating
  • User Count: Number of user ratings

  1.Develop a regression model that links global sales to video game reviews. Regression Analysis代写

Explore ways in which the model fit could be improved through suitable changes to the model specification and variables.

a.Present the final model and results.

b.Explain how you developed your model (what was your initial model, what were the key variations you tried and how did you arrive at the final model – and the thought process behind these steps).

c. Interpret the model results.Regression Analysis代写

      2.For the model you constructed, verify whether the various regression assumptions discussed in class are satisfied. Regression Analysis代写

If an assumption is violated, discuss how it can be handled, and implement the same. Discuss whether this change had a practically significant impact on your model results.

     3.Submit your answers either as one word document (with the SAS code and relevant output) or as a zipped folder containing the different files clearly named.

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