Full question :
The Tasty Sub Shop Case:
A business entrepreneur uses simple linear regression analysis to predict the yearly revenue for a potential restaurant site on the basis of the number of residents living near the site. The entrepreneur then uses the prediction to assess the profitability of the potential restaurant site.
And
The QHIC Case:
The marketing department at Quality Home Improvement Center (QHIC) uses simple linear regression analysis to predict home upkeep expenditure on the basis of home value. Predictions of home upkeep expenditures are used to help determine which homes should be sent advertising brochures promoting QHIC’s products and services.
Discuss the difference in the type of prediction in both cases and provide rational of the reasons that these predictions were used.
Answer and explanation:
In the first case, The Tasty Sub Shop Case, the entrepreneur aims to utlilize the predicted values from his regression analysis in ascertaining profit of his potential business. He does this using the values from number of residents in the area(independent variables) to predict the revenue for his business(dependent variables). His predictions using the number of residents in the area are largely because the residents in the area are his target consumers and are the ones to buy food from his restaurant and increase his revenue.
In the other case, the marketing department in QHIC utilizes the predicted values in determining their customers who need to be aware of their products. They get the predicted values(home upkeep expenditure and dependent variable) by plotting their relationship with home value(independent variable) and then use predicted values of home upkeep expenditures in determining their customers who they will market their products to. They do this because predicting home upkeep expenditures will enable them determine what homes can afford or will need their products and services.
one utilizes his predictions at ascertaining profit while the other uses his predictions in determining potential customer base to market products to. The first case is making a revenue/ profitability prediction while the other is making a market prediction