Deliverable 4 – Predictive Analysis for Data-driven Decisions
You are the manager of a local retail store. To help make decisions within your organization, you recently completed your MBA with an emphasis in business analytics. You have developed the following estimated regression equation to help make data-driven decisions for the store.
Y = 22,100 – 412×1 + 818×2 – 93×3 – 71×4
· Y = weekly sales
· x1 = local unemployment rate
· x2 = weekly average high temperature
· x3 = number of activities in the local community
· x4 = average price of gasoline per gallon
Use the above equation and information to answer the following questions in a Word document, and create a guideline to use for future business decisions:
- Based on the equation above, please provide the value for x1, x2, x3, and x4. Also, explain what these values mean in the context of this question. For example: What does the value of 818 mean in the equation above (specify if it is x1 or x2 or x3 or x4, and explain what those values mean based on the equation and context)?
- What are the estimated weekly sales if the unemployment rate is 3.7%, the average high temperature is 670, there are 10 activities, and the average price of gasoline is $3.39 per gallon?
- What recommendations or decisions could you make based on the predictive analysis in question 2?
Clearly and strongly, used correlation and regression analysis techniques to examine relationships (thoroughly explained values based on the equation and context).
Skillfully evaluated data mining techniques used to enhance managers’ decision-making (estimated weekly sales based on values given).
Clearly and strongly utilized predictive modeling to propose business recommendations, using clear examples in a well-analyzed guideline, and based on predictive analysis in question 2.