A small business has 10 weeks of sales data; the owner would like to determine the best forecasting method for the next period, week 11. Please use 4 methods: 3 period moving average, 4 period moving average, exponential smoothing (a=.3) and weighted moving average with the most recent week, Wt = 0.5, Wt-1 = 0.3 and the oldest week Wt-2= 0.2.

Assignment 4- Forecasting

 

 

For this assignment, you will be working with basic forecasting skills and determining the forecasts using 4 different methods (3 period moving average, 4 period moving average, weighted moving average and simple exponential smoothing) followed by a problem that will use line equations to determine the best fit for a causal model. After finding the forecasts, you will determine the error measures and plot the forecasts against the actual data. All the data is provided on the spreadsheet labeled Assignment 4 Data in D2L. Please complete your work on the spreadsheet and provide a word document explaining your answers.

 

Problem A: Comparison of 4 Methods

A small business has 10 weeks of sales data; the owner would like to determine the best forecasting method for the next period, week 11. Please use 4 methods: 3 period moving average, 4 period moving average, exponential smoothing (a=.3) and weighted moving average with the most recent week, Wt = 0.5, Wt-1 = 0.3 and the oldest week Wt-2= 0.2.

 

Please make sure that you are not typing numbers into formulas rather call out the cell where Alpha or the weights are located. Also, use the function (=Round ) to round all your forecasts to the nearest whole number before performing further calculations.

 

After doing the forecast for any available period, find the MAD and MFE using only comparable periods i.e., if you have 10 weeks of forecast for simple exponential smoothing and others only have 6 weeks, then only average the same 6 weeks together so we compare apples to apples. Plot the actual data on a line chart along with all 4 forecasts- this chart should be on a separate workbook and clearly labeled.

  • What is the best forecast method for the data and why?
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