Mba statistics, data analysis and decision modeling homework
The first step is to select the independent variable , which should include both numerical (such as price, quantity etc ) and categorical (seasonal indicator) features . The latter may refer to a specific month or quarter depending on what type of seasonality is being measured. In this case, let us assume that we are looking at quarterly seasonality over the last three years.
The dependent variable will be total sales over each quarter for each respective year . Next , a regression model must be built using these two variables so that it captures all the nuances associated with seasonal patterns . For instance , an exponential trend line can be used to fit the data points in order to identify any potential outliers or anomalies .
Once this is done , we can compare projected results against actual ones from past quarters in order to assess accuracy of our predictions . If necessary additional factors such as market conditions or external influences may also need to be included in order refine forecasts even further .
In conclusion, building a multiple regression model incorporating categorical variables like seasonal indicators provides companies with valuable insights into expected behavior of future sales performance based on past trends while allowing them to adjust their operations accordingly.