Forecasting (10 problems)

Use exponential smoothing with = 0.3 to forecast the battery sales. Assume the forecast for January was 22 batteries. Highlight your forecast for May.

Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are as follows for the past 12 weeks:

a) Assuming an initial forecast for week 1 of 17,000 miles, use exponential smoothing to compute miles for weeks 2 through 12. Use a =0.2.

b) What is the MAD for this model?

c) Compute the RSFE and tracking signals. Are they within acceptable limits?

The number of pizzas ordered on Friday evenings between 5:30 and 6:30 at a pizza delivery location for the last 10 weeks is shown below. Use exponential smoothing with smoothing constants of .2 and .8 to forecast a value for week 11 (i.e., prepare two forecasts using each of the alpha values). Compare your forecasts using MSE. Which smoothing constant does a better job using lower MSE as the criterion?

58, 46, 55, 39, 42, 63, 54, 55, 61, 52

Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15. Forecast sales for the next day using a 2-day moving average.

A trend line for the attendance at a restaurant’s Sunday brunch is given by

Number = 264 + .72(t)

How many guests would you expect in week 20?

Regression was used to develop a model to predict sales based on advertising dollars spent. The equation developed is Y = 1000 + 20X, where X is advertising dollars and Y is sales. If $300 is spent on advertising, what would be the best prediction for sales?

Use the sales data given below to determine:

(a) The least squares trend line

(b) the predicted value for 1982 sales

Consider the quarterly sales given in the table below.

a. Draw a time series plot for this data set and describe any trend and seasonal behavior that you see.

b. Plot the moving average values on the same graph as the original data. (4 quarters)

c. Find the seasonal index for each quarter. Which is generally the best quarter for sales?

d. Plot the seasonally adjusted series with the original data.

e. Find the regression equation to predict the long-term trend in seasonally adjusted sales for each time period. Does the trend equation show a significant trend over time.

The following data is retail sales for the ABC Company.

a. Compute a regression line for the data to predict sales by month for the year 2000.

b. Calculate monthly seasonal indices for each month.

c. Compute a seasonally adjusted forecast for each month in 2000.

Victor Anderson, the owner of Anderson Belts, Inc., is studying absenteeism among his employees. His workforce is small, consisting of only five employees. For the last three years he recorded the following number of employee absences, in days, for each quarter.

Determine a typical seasonal index for each of the four quarters.