Managerial Decision Modeling w/ Spreadsheets, 3e (Balakrishnan/Render/Stair)
Chapter 11 Forecasting Models
11.1 Chapter Questions
1) Consider the following data that was fitted using a Linear Trend.
Period
Actual value (or) Y
Period number (or) X
Period 1
10
1
Period 2
11
2
Period 3
9
3
Period 4
12
4
Period 5
13
5
Period 6
12
6
Period 7
15
7 The intercept of the trend line is 8.714, and the slope is 0.75. What is the forecast for period 8?
A) 13.714
B) 14.714
C) 15.714
D) 16.714
E) 15.75
Answer: B
Page Ref: 495
Topic: Trend and Seasonality in Time-Series Data
Difficulty: Moderate
AACSB: Analytic Skills
2) Which of the following is considered to be a category of forecasting models?
A) Qualitative
B) Time-series
C) Causal
…show more content…
What is the Mean Absolute Deviation (MAD)?
Period
Error
1
-2
2
1
3
3
4
0
5
-1
6
2
7
4
A) 1
B) 1.86
C) 7
D) 13
E) 5
Answer: B
Page Ref: 478
Topic: Measuring Forecast Error
Difficulty: Moderate
13) Consider the following time series data. Suppose that you use exponential smoothing with an alpha of 0.7 to fit a forecasting model. The forecast for period 7 is
Period
Forecast
Actual value
Period 1
10
10
Period 2
10
11
Period 3
10.7
9
Period 4
9.51
12
Period 5
11.253
13
Period 6
12.476
11
A) 10.443
B) 12
C) 9.443
D) 12.443
E) 11.443
Answer: E
Page Ref: 489
Topic: Basic Time-Series Forecasting Models
Difficulty: Moderate
14) The least squares method for linear regression:
A) minimizes the sum of the errors
B) minimizes the sum of the squared errors
C) maximizes forecasting accuracy
D) minimizes the value of the coefficient of determination R2
E) minimizes the regression equation coefficients
Answer: B
Page Ref: 495
Topic: Trend and Seasonality in Time-Series Data
Difficulty: Moderate
15) Suppose that you intend to use Solver to compute the optimal weights for a weighted moving average. Changing variable cells would refer to:
A) the MAD cell
B) the MSE cell
C) the MAPE cell
D) the weights cells
E) the forecast cells
Answer: D
Page Ref: 487
Topic: Basic Time-Series Forecasting Models
Difficulty: Challenging
16) A time series which
4. Based on your analysis in (1) – (3) above, what is your overall conclusion regarding the
To compute the 90% prediction interval for all trading days during the study period, the formula ( , ) can be used. Referring to the question equals 0.1 and equals 0.05.
a. If the CPI was 110 last year and is 121 this year, what is
6. Although you are basically satisfied with the analysis thus far, you are concerned about the
Critically evaluate the assumptions on which your forecasts are based. What developments could alter your results? Is Mr. Cowins correct in his belief that Hampton can repay the loan in December?
* Now, assume you have acquired some time series data that would enable you to make short, medium, and long term forecasts. Ascertain the quantitative technique that will provide you with the most accurate forecast. Provide a rationale for your responses
A) The weekly budget is formed by only using the early start times of each activity.
This gives the production manager a 62.5% prediction that the economy will be weak and an 83.3% prediction that economy will be strong.
5) Graph the equation you wrote in step four superimposed over the original data. Comment on how well or how poorly the equation fits the data.
13) Refer to the table. What is the average number of customers in the queue plus the number being served?
1. In the last five years the growth in sales for the company has been around 10% per annum, except for the 1997, the growth was 18.78%. In the case, nothing is mentioned that company has made any drastic changes in its strategy to grow faster. In such a scenario, projected a consistent growth of 20% per annum for the next 5 years is too optimistic.
Exercises 12.17, 12.21, and 12.43 require the use of the “Regression” function within the Data Analysis menu in Excel. Refer to Appendix E12 for instructions on using Excel for these exercises.
The weighted average was used to obtain data for product one. This method was used because the most recent weeks have the highest likelihood of predicting the upcoming weeks. It is low cost and easily obtained and it is more reflective of the recent occurrences. A simple naive forecasting was used to calculate the second product. This method relies on intuition and takes into account the recent trends. This method was used because of its simple application.
* As stated in the guidelines, we also assume that the mean of the demand is equal to the product of the mean of the forecasting error and the forecast itself, and the same for the standard deviation of demand;
Business forecasting is the process of studying historical performance for the purpose of using the information gained to project future business conditions so that decisions can be made today that will assist in the achievement of certain goals. Forecasting involves taking historical date and using it to project future data with a mathematical model. Forecasts are extensively used to support business decisions and direct the work of operations managers. In this paper I will introduce different types of forecasting techniques.