Assignment 2: Correlation, simple linear, and Multiple
Regression Analysis 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 in?uence on dependent variables. such as sales. Saies 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 1!} 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 ?t the data well? Run a muitipie regression using all three independent variables. Interpret the multiple regression- Does the regression fit the data well? Does each predictor play a signi?cant role in explaining the signi?cance of the regression? Are some predictors not useful? – If so. did you consider removing those and rerunning the regression? – Are the predictors related too signi?cantiy to one another? What is the
coef?cient of correlation “r"? Do you think this ‘r” value suggests a strong
correlation among the predictors { the independent variables?
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