One of the warehouse managers wants to know if it is possible to predict the number of damaged items per day in the warehouse from the total number of items picked and the number of pickers employed. You decide to use linear regression.
1. State the dependent and independent variables.
2. You collect relevant data and carry out the regression analysis. You obtain an adjusted R2 of 0.78. How would you explain what this means (as far as the performance of the model is concerned) in plain English to the management of the company? You must use your own words; definitions are not acceptable.
3. The warehouse manager asks you to explain why significance tests have been undertaken and what the P-value means. In your own words what would you tell him? You must use your own words; definitions are not acceptable.
4. In the regression model the coefficient for ‘items picked’ is 0.06, the coefficient for ‘number of pickers’ is -8.5 and the value of the intercept is 5.3. If you expect 10 pickers to arrive for work tomorrow and the total number of items that need to be picked is 5000, what is the predicted number of damaged items? Comment on the relationship between these variables and usefulness of this model.
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