Practice Problems: Chapter 4, Forecasting

Chapter 4: Forecasting

No trend and no seasonality models

1.  Auto sales at Carmen’s Chevrolet are shown below. Prepare a time-series plot. Find a Naive forecast for week 7. Compute the MAD and MAPE values.

2.  Auto sales at Carmen’s Chevrolet are shown below. Find a 2 and 3-week and moving average forecasts for week 7. Compute the MAD and MAPE values.

3.  Carmen’s decides to forecast auto sales by weighting the three weeks with a weight of 2 for last week, 1 for two weeks ago and 1 for 3 weeks ago.

4.  Carmen’s decides to forecast auto sales Exponential smoothing with a = 0.8. Assume initial of 10.

Models for time series with trend and no seasonality

5.  Plot the sales data given below. Find a forecast for year 2003 using Naïve model.

Naïve forecast: Ft+1 = At + (At – At-1)

6.  Use the sales data given below to determine: (a) the least squares trend line, and (b) the predicted value for 2003 and 2004 sales. To minimize computations, transform the value of x (time) to simpler numbers. In this case, designate year 1996 as year 1, 1997 as year 2, etc.

Forecast for year 2003 and 2004

Forecasts with seasonality

7.  The following table shows sales data for water pumps sold by a manufacturer. Fid the Naïve forecast for Spring and Summer of Year 5.

Naïve forecast:

8.  The following table shows sales data for water pumps sold by a manufacturer. Find Seasonal Relatives using the simple average method.

9.  Deseasonalize the water pump sales data from problem #8 using the SA index. Find Naïve forecast for Trend with the deseasonalized data. Then find a final forecast adjusted for seasonality for the next quarter using the SA index from problem #8.

Tracking Signal

10.  Given the forecast demand and demand for fishing boats, compute the tracking signal.

Et = Error = Demand - Forecast

|Et| = Absolute error = |Demand – Forecast|

CFEt = Running Sum of Et

CAEt = Running Sum of |Et|

MADt = Running MAD for period t = CAEt/ No. of error

Tracking Signal = CFEt/MADt

Associative Forecast

Regional Foods, Inc. sells organic soap products. A random sample of advertising expense in thousand dollars for eight randomly selected months and corresponding sales in million dollars is given below. Using the Associative model ausal approach determine a forecast for the next month if the company is considering spending $15,000 on advertising. What is the expected sales if the advertising is $22,500?

11