MGT 301- Ch 4 Prep and Practice
A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 150, and 130. The average over all months is 190. The approximate seasonal index for July is:
0.684 Step 1 - Calculate average historical demand. To do this, we must first obtain the actual demand during July (in this case 110, 150, 130) and divide by the number of months on record (in this case 3). Thus, average July demand is calculated as 110 + 150 + 130 = 390/3 = 130 Step 2 - Calculate seasonal index by taking monthly average (130) and dividing by average demand over all months (190). Seasonal index for July is 130/190 = 0.684
Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naïve forecast?
1.0
Given an actual demand of 103, a previous forecast value of 99, and an alpha of .4, the exponential smoothing forecast for the next period would be:
100.6 Last period's forecast + α(Last period's demand - last period's forecast), where α = the smoothing constant. Therefore, in this case:
Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?
1000 units
If demand is 106 during January, 120 in February, 134 in March, and 142 in April, what is the 3-month simple moving average for May?
132 120+134+142 = 396 396/3 = 132 Moving Average = 132
The last four months of sales were 8, 10, 15, and 9 units. The last four forecasts were 5, 6, 11, and 12 units. The Mean Absolute Deviation (MAD) is:
3.5
Given forecast errors of -1, 4, 8, and -3, what is the mean absolute deviation?
4 1+4+8+3=16 16/4=4
A time-series trend equation is 25.3 + 2.1X. What is your forecast for period 7?
40
Given the following data about monthly demand, what is the approximate forecast for May using a four month moving average? November = 39 December = 36 January = 40 February = 42 March = 48 April = 46
44
Given an actual demand of 61, a previous forecast value of 58, and an alpha of .3, the exponential smoothing forecast for the next period would be:
58.9
Given last periods forecast of 65, and last periods demand of 62, what is the simple exponential smoothing forecast with an alpha of .4 for the next period?
63.8
Practice in Excel file
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The primary purpose of the mean absolute deviation (MAD) in forecasting is to: A. measure forecast accuracy. B. remove random variations. C. estimate the trend line. D. eliminate forecast errors. E. seasonally adjust the forecast.
A
Which forecasting model is based upon salespersons' estimates of expected sales? A. sales force composite B. jury of executive opinion C. Delphi method D. market survey
A
Which of the following is a quantitative forecasting method? A. exponential smoothing. B. sales force composite C. market survey D. jury of executive opinion
A
What is a data pattern that repeats itself after a period of days, weeks, months, or quarters? A. cycle B. seasonality C. trend D. random variation
B
Which of the following is a qualitative forecasting method? A. trend projection B. Delphi method C. linear regression D. naive approach
B
Which of the following statements is NOT true regarding forecasting? A. Forecasting is the art and science of predicting future events. B. Forecasting is exclusively an objective prediction. C. A forecast is usually classified by the future time horizon that it covers. D. Forecasting may involve taking historical data and projecting them into the future with a mathematical model.
B
The last four weekly values of sales were 80, 100, 105, and 90 units. The last four forecasts were 60, 80, 95, and 75 units. These forecasts illustrate:
Bias
The forecasting time horizon that would typically be easiest to predict for would be the A. medium range. B. long range. C. short range. D. intermediate range.
C
"Today's forecast equals yesterday's actual demand" is referred as A. exponential smoothing. B. a moving average. C. the naive approach. D. the Delphi method.
C
A six-month moving average forecast is generally better than a three-month moving average forecast if demand: A. follows an upward trend. B. follows a downward trend. C. exceeds one million units per year. D. is rather stable. E. has been changing due to recent promotional efforts.
D
A forecast that projects a company's sales is a(n):
Demand Forecast
Quantitative methods of forecasting include
Exponential smoothing
Which of the following statements about time-series forecasting is true?
It is based on the assumption that the analysis of past demand helps predict future demand.
The primary purpose of the mean absolute deviation (MAD) in forecasting is to:
Measure Forecast accuracy
`Which time-series model assumes that demand in the next period will be equal to the most recent period's demand?
Naive Approaach
Forecasts are usually classified into three categories including:
Short-range, medium-range, and long-range
Which of the following uses three types of participants: decision makers, staff personnel, and respondents?
The Delphi method
A regression model is used to forecast sales based on advertising dollars spent. The regression line is y=500+35x and the coefficient of determination is .90. Which is the best statement about this forecasting model?
The correlation between sales and advertising is positive.
The degree or strength of a relationship between two variables is shown by the__________
correlation coefficient
For a given product demand, the time-series trend equation is 53 - 4X. The negative sign on the slope of the equation:
is an indication that product demand is declining
Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a__________
long range time horizon
The tracking signal is the__________
ratio of cumulative error/MAD
Time-series patterns that repeat themselves after a period of days or weeks are called
seasonality