- Submit one Excel file with your answers for the following questions ((a)-(e)).
- In your Excel file create three worksheets:
- P4-(b): regression report for part (b)
- P4-(d): regression report for part (d)
- Answers: all answers for part (a) - (e)
The following data contains the monthly number of airlines tickets sold by a travel agency for four years
Our goal is to build a regression model to predict the demand for the following 12 months.
a) Does a linear trend appear to fit these data well? Explain why or why not. Reference any tables/figures that you need to make your point.
b) Build a linear trend model or nonlinear trend regression model (depending on your answer in part a). Do not add a seasonality factor to this model. To validate your model, use the last 12 months as a validation data set.
- Display the regression output as 'P4 (b)' in your Excel file. Attach the plot of the fitted values and the actual values over time in worksheet ‘Answer’ in your Excel file.
- Fill in the table below with your predictions and errors. What are the RMSE and MAPE of the trend model based on the validation data? Display the results in the worksheet ‘Answer’.
c) Is there evidence of some seasonal pattern in the sales data? If so, characterize the seasonal pattern (monthly, quarterly, or yearly) with the number of seasons.
d) Build a regression model with trend and seasonality. To validate your model, use the last 12 months as a validation data set.
- Display the regression output as 'P4-(d)' in your Excel file. Attach the plot of the fitted values and the actual values over time in worksheet ‘Answer’ in your Excel file.
- Fill in the table below with your predictions and errors. What are the RMSE and MAPE of the trend model based on the validation data? Display the results in the worksheet ‘Answer’. Need to show me how to arrive at answer not just the answer - Steps by steps
