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Forecasting for WidgeCorp: Applied Managerial Decision-Making

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WidgeCorp is considering branching out into cold beverages. You have been asked to come up with a regression model to forecast monthly sales of cold beverages for the next year. Think about what variables you might include in your model. Please research about regression analysis, and provide detailed discussion about various types of regression including simple and multiple regression as well as linear and non-linear regression along with real world examples and at least three references. Also, explain how regression analysis and its methods can help WidgeCorp with its cold beverage sales.

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Solution Summary

This posting develops a forecasting model based for WidgeCorp on regression model. Then the solution develops a multiple regression model for WidgeCorp. 766 words with 3 references.

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STEP 1
Simple regression:
In this regression the relationship between the selected values and observed value is established so that the most probable value of the observed variable can be predicted from the values of the selected variable. Usually the selected variable is x and the observed variable is y. The selected variable is called the independent variable, the predictor, the input or the carrier. On the other hand the observed value is called the dependent variable, predicted variable, the output or the response. In case of WidgeCorp the sales of cold beverages can be dependent on the marketing budget of WidgeCorp for cold beverages. The greater the marketing budget the greater the sales of cold beverages. So in this case it would be regression of sales of cold beverages on the marketing budget.

STEP 2
Multiple regression:
In this regression the relationship between two or more selected independent variables and the observed value is established so that the most probable value of the observed value can be predicted from the values of the selected variables. This is an analysis where more than one independent variables influence the dependent variable. The multiple ...

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