Chapter 4 Answers
Chapter 4_class exercise
True/False
1. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product.
Answer: TRUE
2. A time-series model uses a series of past data points to make the forecast.
Answer: TRUE
3. Cycles and random variations are both components of time series.
Answer: TRUE
4. One advantage of exponential smoothing is the limited amount of record keeping involved.
Answer: TRUE
5. If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased.
Answer: TRUE
Multiple Choice Questions
1. Forecasts
A) become more accurate with longer time horizons
B) are rarely perfect
C) are more accurate for individual items than for groups of items
D) all of the above
E) none of the above
Answer: B
2. Which of the following is not a step in the forecasting process?
A) Determine the use of the forecast.
B) Eliminate any assumptions.
C) Determine the time horizon.
D) Select forecasting model.
E) Validate and implement the results.
Answer: B
3. Which of the following statements about time-series forecasting is true?
A) It is based on the assumption that future demand will be the same as past demand.
B) It makes extensive use of the data collected in the qualitative approach.
C) It is based on the assumption that the analysis of past demand helps predict future demand.
D) Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than associative forecasting.
E) All of the above are true.
Answer: C
4. Time-series data may exhibit which of the following behaviors?
A) trend
B) random variations
C) seasonality
D) cycles
E) They may exhibit all of the above.
Answer: E
5. The fundamental difference between cycles and seasonality is the
A) duration of the repeating patterns
B) magnitude of the variation
C) ability to attribute the pattern to a cause
D) all of the above
E) none of the
True/False
1. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product.
Answer: TRUE
2. A time-series model uses a series of past data points to make the forecast.
Answer: TRUE
3. Cycles and random variations are both components of time series.
Answer: TRUE
4. One advantage of exponential smoothing is the limited amount of record keeping involved.
Answer: TRUE
5. If a forecast is consistently greater than (or less than) actual values, the forecast is said to be biased.
Answer: TRUE
Multiple Choice Questions
1. Forecasts
A) become more accurate with longer time horizons
B) are rarely perfect
C) are more accurate for individual items than for groups of items
D) all of the above
E) none of the above
Answer: B
2. Which of the following is not a step in the forecasting process?
A) Determine the use of the forecast.
B) Eliminate any assumptions.
C) Determine the time horizon.
D) Select forecasting model.
E) Validate and implement the results.
Answer: B
3. Which of the following statements about time-series forecasting is true?
A) It is based on the assumption that future demand will be the same as past demand.
B) It makes extensive use of the data collected in the qualitative approach.
C) It is based on the assumption that the analysis of past demand helps predict future demand.
D) Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than associative forecasting.
E) All of the above are true.
Answer: C
4. Time-series data may exhibit which of the following behaviors?
A) trend
B) random variations
C) seasonality
D) cycles
E) They may exhibit all of the above.
Answer: E
5. The fundamental difference between cycles and seasonality is the
A) duration of the repeating patterns
B) magnitude of the variation
C) ability to attribute the pattern to a cause
D) all of the above
E) none of the