The following Demand Forecasting Methods MCQs have been compiled by our experts through research, in order to test your knowledge of the subject of Demand Forecasting Methods. We encourage you to answer these multiple-choice questions to assess your proficiency.

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A. Delivery safety

B. Order fill rate

C. Service recovery

D. Additive model

A. Centered moving average method

B. Coefficient of determination method

C. Correlation coefficient method

D. None of these

A. Measures the strength of the relationship between two variables

B. Sum of the differences between the actual and the forecasted demand values

C. The proportion of variation explained by regression

D. Both b & c possible

A. –∞ & +∞

B. 0 & +1

C. 1 & +∞

D. –1 & +1

A. Cumulative sum error

B. Correlation coefficient

C. Cyclical variations

D. Damped trend

A. Cumulative sum error

B. Correlation coefficient

C. Cyclical variations

D. Damped trend

A. Decreases initially

B. Increases initially

C. Both a & b

D. None of these

A. Delphi method

B. Dependent method

C. Correlation method

D. Coefficient method

A. Delphi method

B. Dependent demand

C. Correlation method

D. Coefficient method

A. True

B. False

A. Measures the strength of the relationship between two variables

B. Sum of the differences between the actual and the forecasted demand values

C. A measure of the variation not explained by the regression model but resulting from other factors or variables

D. Both b & c possible

A. Exponential growth

B. Expert opinion

C. Exponential smoothing

D. None of these

A. Exponential growth

B. Expert opinion

C. Exponential smoothing

D. None of these

A. Exponential growth

B. Expert opinion

C. Exponential smoothing

D. None of these

A. Historical life-cycle analogy

B. Independent demand

C. Independent or predictor variable

D. Exponential growth

A. Historical life-cycle analogy

B. Independent demand

C. Independent or predictor variable

D. Exponential growth

A. Independent variable

B. Independent demand

C. Independent or predictor variable

D. Exponential growth

A. Uncommon factors

B. Common factors

C. General factors

D. Specific factors

A. Leading indicators

B. Independent demand

C. Independent or predictor variable

D. Exponential growth

A. Draw the line of best fit in linear regression

B. Draw the line of best fit in Logistic Regression

C. Draw the line of best fit in Ridge Regression

D. All are Correct

A. Dependent variable and one or more independent variables

B. Independent variable and one or more independent variables

C. Both a & b

D. None of these

A. Either increases or decreases

B. Nor increases or decreases

C. Only increase

D. Only decrease

A. Linear trend multiplicative method

B. Delphi method

C. Correlation method

D. Coefficient method

A. Mutually Assured Destruction

B. Mean Absolute Deviation

C. Make A Difference

D. None of these

A. Mean absolute percentage error

B. Mean squared error

C. Mean squared error

D. Moving average

A. True

B. False

A. Sum of the differences

B. Sum of the squared differences

C. Divided of the squared differences

D. None of these

A. True

B. False

A. One independent variable

B. Two independent variables

C. Several independent variables

D. Some independent variables

A. Functional components

B. Class components

C. Seasonal components

D. None of these

A. Naïve approach

B. Nonlinear trend

C. Qualitative method

D. None of these

A. Naïve approach

B. Nonlinear trend

C. Qualitative method

D. None of these

A. Naïve approach

B. Nonlinear trend

C. Qualitative method

D. None of these

A. True

B. False

A. Regression sum of squares

B. Naïve approach

C. Nonlinear trend

D. Qualitative method

A. During the Month

B. During the weak

C. During the DAY

D. During the year

A. Naïve approach

B. Simple average method

C. Qualitative method

D. None of these

A. True

B. False

A. Time series

B. Total sum of squares

C. Tracking signals

D. None of these

A. Tracking signals

B. Total sum of squares

C. Tracking signals

D. None of these

A. Tracking signals

B. Total sum of squares

C. Tracking signals

D. Trend

A. Exploratory factor

B. Confirmatory factor

C. Trend factor

D. Both a & b

A. Medium-term time series

B. Long-term time series

C. Short-term time series

D. Large-term time series

A. Qualitative method

B. Expert opinion

C. Delphi method

D. Historical life-cycle analogy

A. Aggregate forecast

B. Simple average

C. Time series

D. Moving average

A. Dependent demand

B. Independent demand

C. Aggregate forecast

D. Actual demand

A. Coefficient of determination

B. Error sum of squares

C. Total sum of squares

D. Regression sum of squares

A. Dependent demand

B. Independent demand

C. Aggregate forecast

D. Actual demand

A. Nonlinear trend

B. Damped trend

C. Linear trend

D. Historical life-cycle analogy

A. Naïve approach

B. Delphi method

C. Time series

D. Aggregate forecast