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Question

In the context of distinguishing between forecasting and prediction, which one of the following statements is false ?

This question was previously asked in
UGC NET 2016 Paper 2 Management Question Paper (22-Jan-2017)
The correct answer is

Forecasting reflects management’s judgement after taking all available information into account; while prediction involves the projection of the past into the future.

 Statement 2 is false — the two halves have been swapped.

The correct distinction :

 ForecastingPrediction
BasisProjection of the past into the future using data and a theoretical modelManagement’s judgement after taking all available information into account — including information the model cannot hold
NatureObjective, systematic, replicableSubjective, intuitive, personal
Error analysisPossible — MAD, MSE, MAPE, tracking signalNot possible, as there is no model against which to measure deviation
RepeatabilityTwo analysts with the same data reach the same figureTwo managers may reach different figures

Statement 2 attributes the projection of the past to prediction and management’s judgement to forecasting. Both attributions are the wrong way round, which is what makes it the false statement.

Why the other three are true.

StatementWhy it stands
1Forecasting rests on a model — time series, regression, exponential smoothing. Prediction may indeed rest on intuition
3Forecast error is measurable precisely because a forecast is generated by a stated method: \(e_{t}=A_{t}-F_{t}\), from which MAD and MSE follow. A hunch yields no such residual
4Prediction is by definition subjective; that is the entire point of the contrast

A caution against overstating the contrast. Prediction is not merely guesswork, and it is not inferior. A forecast can only extrapolate relationships present in past data, so it is blind to a structural break — a new competitor, a change of law, a technological shift. That is exactly where a manager’s judgement is indispensable, and it is why the best practice is to combine the two: generate a statistical forecast, then adjust it judgementally for information the data cannot yet contain.

The forecasting methods themselves divide the same way: quantitative methods — time-series and causal — require historical data, while qualitative methods such as the Delphi technique, expert opinion, sales-force composite and market research are used precisely when data are absent, as with a new product.

Hence, the answer is statement 2.

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