Correlation, simple linear, and Multiple Regression Analysis

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Multiple regression analysis is widely used in  business
research in order to forecast and predict purposes. It is also used to
determine what independent variables have an influence on dependent
variables,  such as sales.


Sales can be attributed to quality, customer  service,
and location. In multiple regression analysis, we can determine which
independent variable contributes the most to sales; it could be quality
or  customer service or location.


Now, consider the following scenario. You have been
assigned the task of creating a multiple regression equation of at least
three  variables that explains Microsoft’s annual sales.


Use a time series of data of at least 10 years. You  can search for this data using the Internet.


Before       running the regression analysis , predict
what sign each variable will be       and explain why you made that
prediction.

 

Run three       simple linear regressions by considering one independent variable at a       time

 

After       running each of the three linear regressions, interpret the regression.

 

Does       the regression fit the data well?

 

Run a       multiple regression using all three independent variables.

 

Interpret       the multiple regression.  Does the       regression fit the data well?

 

Does       each predictor play a significant role in explaining the significance of       the regression?

 

Are       some predictors not useful?

 

If so,       did you consider removing those and rerunning the regression?

 

Are the       predictors related too significantly to
one another? What is the coefficient       of correlation “r”? Do you
think this “r” value suggests a strong       correlation among the
predictors ( the independent variables?

 

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Correlation, simple linear, and Multiple Regression Analysis

Click here to order similar paper @Essaybay.net. 100% Original.Written from scratch by professional writers.


Click here to order similar paper @Essaybay.net. 100% Original.Written from scratch by professional writers.

 

Multiple regression analysis is widely used in business research in order to forecast and predict purposes. It is also used to determine what independent variables have an influence on dependent variables, such as sales.

Need a Professional Writer to Work on this Paper and Give you Original Paper? CLICK HERE TO GET THIS PAPER WRITTEN

Sales can be attributed to quality, customer service, and location. In multiple regression analysis, we can determine which independent variable contributes the most to sales; it could be quality or customer service or location.

Now, consider the following scenario. You have been assigned the task of creating a multiple regression equation of at least three variables that explains Microsoft’s annual sales.

Use a time series of data of at least 10 years. You can search for this data using the Internet.

  • Before running the regression analysis , predict what sign each variable will be and explain why you made that prediction.
  • Run three simple linear regressions by considering one independent variable at a time
  • After running each of the three linear regressions, interpret the regression.
  • Does the regression fit the data well?
  • Run a multiple regression using all three independent variables.
  • Interpret the multiple regression.  Does the regression fit the data well?
  • Does each predictor play a significant role in explaining the significance of the regression?
  • Are some predictors not useful?
  • If so, did you consider removing those and rerunning the regression?
  • Are the predictors related too significantly to one another? What is the coefficient of correlation “r”? Do you think this “r” value suggests a strong correlation among the predictors ( the independent variables?

Submit your answers in a two- to three-page Word document

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