Chapter 19
1. Mark the correct statement.
(a) Since future is uncertain, forecasting has absolutely no useful role.
(b) Qualitative models of forecasting make no use of numbers at any stage.
(c) Qualitative models employ personal judgement and involve qualities like intuition and
judgement.
(d) Delphi method is illustrative of quantitative models.
2. Which of these is not true about time series models of forecasting?
(a) They attempt to predict the future on the basis of historical data.
(b) They hold the future to be a continuum of the past.
(c) They are based on the premise that what would happen in future is a function of what has
happened in the past.
(d) They are based on the past, present, and future conditions.
3. Mark the wrong statement.
(a) Qualitative forecasting is always better than quantitative forecasting.
(b) Delphi method is a method of qualitative forecasting.
(c) Quantitative forecasting methods are objective in nature.
(d) Consumer panels are used by marketing research methods.
4. Mark the wrong statement.
(a) Delphi method is an iterative group process that employs a group of experts.
(b) In Delphi method of forecasting, the experts are usually not known to each other.
(c) Exponential smoothing is a time-series model of forecasting.
(d) Time-series models are so called since they make possible forecasting at regular intervals
of time.
5. Which of the following is not true about time-series?
(a) It refers to time-based data.
(b) It consists of four components: secular trend, seasonal variations, cyclical variations and
random variations.
(c) Forecasting with it implies that predictions about the future values are made only from
past data.
(d) It can be broken down into explained and unexplained variations.
6. Mark the correct statement.
(a) An n-period simple moving average gives a weightage of 1/n to each value included in
the average.
(b) Weighted moving average gives equal weightage to the various values under
consideration.
(c) For a given time-series set of data, the weighted average values would be consistently
higher than simple moving average values.
(d) In the 3-month moving average, the first forecast would be for the month 2 and calculated
as simple average of months 1, 2 and 3.
7. Which of these is not correct about exponential smoothing?
(a) In this technique of forecasting, the forecasted value for a period is calculated as the
weighted average of all the previous values.
(b) Successive weightage of preceding time periods are declining.
(c)  is called the smoothing constant.
(d) Summation of weights is equal to 1 if  is low (less than 0.5) and more than 1 if  is high
(more than 0.5).
8. Which of these is not correct?
(a) In exponential smoothing, current forecast is obtained by adjusting the previous forecast
by a fraction of the forecast error.
(b) Forecast error = Forecasted value – Actual value
(c) A high value of  gives relatively large weightage to recent value while a low value gives
relatively low weightage.
(d) The weights used in exponential smoothing are  + (1 - ) + (1 - )2 + …
9. Mark the wrong statement.
(a) MAD is equal to summation of forecast errors divided by n, where forecast error is the
excess of actual value over forecast value.
(b) If choice between two values of smoothing constant () is to be made, the one with
lower MAD should be preferred.
(c) Mean squared error is the average of the squared differences between the actual and
forecasted values.
(d) MAPE is the mean of absolute differences between actual and forecasted values,
expressed as a percentage of the actual values.
10. Mark the wrong statement.
(a) In time-series data, fitting trend line to the given data makes future projections.
(b) Regression analysis deals with making forecasts about one or more dependent variables
on the basis of one or more independent variables.
(c) Explained variation is that component of total variation which is explained by the line of
relationship.
(d) The ratio of explained variation to total variation is called co-efficient of determination.