Multiple regression

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Question description

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?

On a separate page, cite all sources using the APA guidelines.

skywalkerus
School: University of Maryland

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Anonymous
Wow this is really good.... didn't expect it. Sweet!!!!

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