# AmeriPlas, Inc., produces 20-ounce plastic drinking cups that are embossed with the names of prominent beers and soft drinks. The

## Question:

AmeriPlas, Inc., produces 20-ounce plastic drinking cups that are embossed with the names of prominent beers and soft drinks. The sales data are:

 Date Sales Jan-13 40,358 Feb-13 45,002 Mar-13 63,165 Apr-13 57,479 May-13 52,308 Jun-13 60,062 Jul-13 51,694 Aug-13 54,469 Sep-13 48,284 Oct-13 45,239 Nov-13 40,665 Dec-13 47,968 Jan-14 37,255 Feb-14 38,521 Mar-14 55,110 Apr-14 51,389 May-14 58,068 Jun-14 64,028 Jul-14 52,873 Aug-14 62,584 Sep-14 53,373 Oct-14 52,060 Nov-14 51,727 Dec-14 51,455 Jan-15 47,906 Feb-15 53,570 Mar-15 69,189 Apr-15 64,346 May-15 77,267 Jun-15 75,787 Jul-15 74,052 Aug-15 79,756 Sep-15 73,292 Oct-15 77,207 Nov-15 68,423 Dec-15 67,274 Jan-16 65,711 Feb-16 68,005 Mar-16 78,029 Apr-16 92,764 May-16 97,175 Jun-16 86,255 Jul-16 90,496 Aug-16 87,602 Sep-16 83,577 Oct-16 92,610 Nov-16 73,949 Dec-16 77,711

a. Prepare a time-series plot of the sales data. Does there appear to be a regular pattern of movement in the data that may be seasonal? Ronnie Mills, the product manager for this product line, believes that her brief review of sales data for the four-year period indicates that sales are slowest in November, December, January, and February than in other months. Do you agree?

b. Since production is closely related to orders for current shipment, Ronnie would like to have a monthly sales forecast that incorporates monthly fluctuations. She has asked you to develop a trend model that includes a time index and dummy variables for all but the above mentioned four months. Do these results support Ronnie’s observations? Explain.

c. Ronnie believes that there has been some increase in the rate of sales growth. To test this and to include such a possibility in the forecasting effort, she has asked that you add the square of the time index (T) to your model (call this new term T2). Is there any evidence of increasing of sales growth? Compare the results of this model with those found in part (b).

d. Use the model in part (c) to forecast sales for 2017. Calculate the mean absolute percentage error (MAPE) for the first six months of 2017. Actual sales for those six months were as shown below:

## This problem has been solved!

Do you need an answer to a question different from the above? Ask your question!

## Step by Step Answer:

Related Book For
Question Details
Chapter # 5
Section: Exercises
Problem: 12
View Solution
Create a free account to access the answer
Cannot find your solution?
Post a FREE question now and get an answer within minutes. * Average response time.
Question Posted: March 09, 2019 12:08:46