Home Chapter 5: Forecasting Self-Study Quizzes Multiple Choice

# Multiple Choice

This activity contains 12 questions.

## If one desires to make a prediction for a point in the distant future, the most appropriate technique is:

 regression analysis. exponential smoothing. time-series. multiple regression analysis. None of the above

## If the actual value for the month of January was 120, and the forecast made for January was 112, what would be the forecast for February if we used a simple exponential smoothing with an α value of 0.3?

 114.4 109.6 122.4 112 none of the above

## The mean absolute deviation error (MAD) will always be:

 positive. between 0 and 1. negative. equal to the tracking signal. None of the above

## In picking an appropriate value for the smoothing constant (α) in a simple smoothing model, the objective is to___________.

 isolate the seasonal component identify the regression slope obtain the most accurate forecast achieve the highest tracking signal possible none of the above

## Given the following data, if MAD = 1.25, the actual demand in period 2 (A2) must have been

 A2 = 3. A2 = 5. A2 = 4.5. A2 = 3.5. either (a) or (b).

## The process of isolating linear trend and seasonal factors to develop more accurate forecasts is called:

 multiple regression. decomposition. linearization. multiplicative model. none of the above

## Positive tracking signals indicate a tendency of demand to __________.

 display a downward trend be lagging behind the forecast be exactly the same as the forecast most of the time be greater than the forecast none of the above

Average starting salaries for students using a placement service at a university have been steadily increasing. A study of the last four graduating classes indicates the following average salaries: \$20,000, \$22,000, \$23,000, and \$25,000 (last graduating class).

Predict the starting salary for the next graduating class using an exponential smoothing model with = 0.2. Assume that the initial forecast was \$20,000 (so that the forecast and the actual were the same).

 \$21,536 \$21,736 \$20,176 \$21,936 None of the above

## Demand for a particular type of battery fluctuates from one week to the next. A study of the last six weeks provides the following demands (in dozens): 4, 5, 3, 6, 7, 8 (last week). Forecast demand during the next week using a two-week moving average.

 8 7 7.5 6 None of the above

## The MAD for the following forecast versus actual sales figures is

 5. 2.5. 3. 4.5. none of the above

## Decomposition is

 a causal forecasting method. a sales force composite forecast method. a qualitative forecasting method. a time-series forecasting model. none of the above

## Decomposition implies the disaggregation of a time series into:

 trend, cycles, and seasonal variations. cycles, average, and random variations. cycles, trend, random variations, and seasonal. any of the above none of the above