1. Which one of the following forecasting techniques is not suited for making forecasts for planning production schedules in the short range?
(a) Moving average
(b) Exponential moving average
(c) Regression analysis
(d) Delphi
(1 Mark, 1988)

Ans: d
2. Which of the following is a technique for forecasting?
(a) Exponential smoothing
(b) PERT/ CPM
(c) Gantt chart technique
(d) Control charts
(2 Mark, 1989)

Ans: a
3. The most commonly used criteria for measuring forecast error is
(a) Mean absolute deviation
(b) Mean absolute percentage error
(c) Mean standard error
(d) Mean square error
(1 Mark, 1997)

Ans: a
4. In a forecasting model, at the end of period 13, the forecasted value for period 14 is 75. Actual value in the periods 14 to 16 are constant at 100. if the assumed simple exponential smoothing parameter is 0.5, then the MSE at the end of period 16 is:
(a) 820.31
(b) 273.44
(c) 43.75
(d) 14.58
(2 Mark, 1997)

Ans: b
5. In a time series forecasting model, the demand for five time periods was 10, 13, 15, 18 and 22. A linear regression fit resulted in an equation F = 6.9 + 2.9 t, where F is the forecast for period t. The sum of absolute deviations for the five data is:
(a) 2.2
(b) 0.2
(c) 1.2
(d) 24.3
(2 Mark, 2000)
6.When using a simple moving average to forecast demand, one would
(a) Give equal weight to all demand data
(b) Assign more weight to the recent demand data
(c) Include new demand data in the average without discarding the earlier data
(d) Include new demand data in the average after discarding some of the earlier demand data
(1 Mark, 2001)

Ans: d
7. A regression model is used to express a variable Y as a function of another variable X. this implies that
(a) There is a causal relationship between Y and X
(b) A value of X may be used to estimate a value of Y
(c) Values of X exactly determine values of Y
(d) There is no causal relationship between Y and X
(1 Mark, 2002)

Ans: b
8. The sale of cycles in a shop in four consecutive months is given as 70, 68, 82, 95. Exponentially smoothing average method with a smoothing factor of 0.4 is used in forecasting. The expected number of sales in the next month is
(a) 59
(b) 72
(c) 86
(d) 136
(2 Mark, 2003)

Ans: b
We know,
{ F }_{ t+1 } = \propto { D }_{ t }+\propto \left( 1\propto \right) { D }_{ t1 }+\propto { { \left( 1\propto \right) }^{ 2 }D }_{ t2 }+\propto { { \left( 1\propto \right) }^{ 3 }D }_{ t3 }
= 0.4\times 95+0.4\times \left( 10.4 \right) \times 82+0.4\times { { \left( 10.4 \right) }^{ 2 }\times 68 }+0.4\times { { \left( 10.4 \right) }^{ 3 }\times 70 } = 73.52
9. For a product, the forecast and the actual sales for December 2002 were 25 and 20 respectively. If the exponential smoothing constant (α) is taken as 0.2, the forecast sales for January 2003 would be
(a) 21
(b) 23
(c) 24
(d) 27
(1 Mark, 2004)

Ans: c
10. The sales of a product during the last four years were 860, 880, 870 and 890 units. The forecast for the fourth year was 876 units. If the forecast for the fifth year, using simple exponential smoothing, is equal to the forecast using a three period moving average, the value of the exponential smoothing constant α is
(a) 1/7
(b) 1/5
(c) 2/7
(d) 2/5
(1 Mark, 2005)

Ans: c
11. In an MRP system, component demand is:
(a) Forecasted
(b) Established by the master production schedule
(c) Calculated by the MRP system from the master production schedule
(d) Ignored
(1 Mark, 2006)

Ans: c
12. Which of the following forecasting methods takes a fraction of forecast error into account for the next period forecast?
(a) Simple average method
(b) Moving average method
(c) Weighted moving average method
(d) Exponential smoothening method
(1 Mark, 2009)

Ans: d
13. A moving average system is used for forecasting weekly demand. F_{1}(t) and F_{2}(t) are sequences of forecasts with parameters m_{1} and m_{2}, respectively, where m_{1} and m_{2} (m_{1} > m_{2}) denote the numbers of weeks over which the moving averages are taken. The actual demand shows a step increase from d_{1} to d_{2} at a certain time. Subsequently,
(a) Neither F_{1}(t) not F_{2}(t) will catch up with the value d_{2}
(b) Both sequences F_{1}(t) and F_{2}(t) will reach d_{2} in the same period
(c) F_{1}(t) will attain the value d_{2} before F_{2}(t)
(d) F_{2}(t) will attain the value d_{2} before F_{1}(t)
(2 Mark, 2008)

Ans: d
14. The demand and forecast for February are 12000 and 10275, respectively. Using single exponential smoothening method (smoothening coefficient = 0.25), forecast for the month of March is
(a) 431
(b) 9587
(c) 10706
(d) 11000
(1 Mark, 2010)

Ans: c
15. In simple exponential smoothing forecasting, to give higher weightage to recent demand information, the smoothing constant must be close to
(a) 1
(b) zero
(c) 0.5
(d) 1.0
(1 Mark, 2013)

Ans: d
16. In exponential smoothening method, which one of the following is true?
(a) 0 ≤ α ≤ 1 and high value of α is used for stable demand
(b) 0 ≤ α ≤ 1 and high value of α is used for unstable demand
(c) α ≥ 1 and high value of α is used for stable demand
(d) α ≤ 0 and high value of α is used for unstable demand
(1 Mark, 2014[1])

Ans: b
18. For a canteen, the actual demand for disposable cups was 500 units in January and 600 units in February. The forecast for the month of January was 400 units. The forecast for the month of March considering smoothing coefficient as 0.75 is ______.
(2 Mark, 2015[1])

Ans: 569
19. Sales data of a product is given in the following table:
Regarding forecast for the month of June, which one of the following statements is TRUE?
(a) Moving average will forecast a higher value compared to regression.
(b) Higher the value of order N, the greater will be the forecast value by moving average.
(c) Exponential smoothing will forecast a higher value compared to regression.
(d) Regression will forecast a higher value compared to moving average.
(2 Mark, 2015[2])

Ans: d
20. The demand for a twowheeler was 900 units and 1030 units in April 2015 and May 2015, respectively. The forecast for the month of April 2015 was 850 units. Considering a smoothing constant of 0.6, the forecast for the month of June 2015 is
(a) 850 units
(b) 927 units
(c) 965 units
(d) 970 units
(2 Mark, 2016[3])

Ans: d
21.The time series forecasting method that gives equal weightage to each of the m most recent observations is
(a) Moving average method
(b) Exponential smoothing with linear trend
(c) Triple Exponential smoothing
(d) Kalman Filter
(1 Mark, 2018[1])

Ans: a