Question 1

A long-range forecast typically covers a planning horizon of 3 to 12 months.

Accepted Answer

False

Question 2

As the value of k is increased in a moving average forecasting model, the forecast reacts more slowly to recent changes in the time series.

Accepted Answer

This is because a larger value of k means that the average is calculated over a longer period of time, so recent changes have less of an impact on the forecast.

Question 3

A major difference between MSE and MAD is that MAD is influenced much more by large forecast errors than by small errors.

Accepted Answer

False

Question 4

In forecasting, irregular variation that is explainable can normally be discarded.

Accepted Answer

The answer of In forecasting, irregular variation that is explainable...

Question 5

An R² of 0.70 mean 30% of the variability in the dependent variable was explained by the independent variable.

Accepted Answer

An R-squared value of 0.70 means that 70% of the variability in the dependent variable is explained by the independent variable, not 30%. Therefore, the statement in the question is false.

Question 6

In a regression model, both the dependent and independent variables must be numerical.

Accepted Answer

Regression models require numerical variables for both the dependent and independent variables in order to calculate the relationship between them. Categorical or qualitative variables cannot be used in a regression model without being converted to numerical values through methods such as dummy coding.

Question 7

Top managers use detailed forecasts of unit sales for individual products
e.g., brands and sizes) for decisions involving financial planning and for sizing and locating new facilities.

Accepted Answer

The answer of Top managers use detailed forecasts of unit...

Question 8

Better operational decisions can be made by integrating forecasting with value chain and capacity management systems.

Accepted Answer

Integrating forecasting with value chain and capacity management systems can help organizations make better operational decisions, as they can better plan for and anticipate demand, allocate resources effectively, and optimize their production processes. By having a more comprehensive view of their operations, they can be more responsive to changes in the marketplace and make decisions that are more aligned with their strategic goals.

Question 9

Long range forecasts expressed in sales dollars are more meaningful to top managers than to managers at the operations level.

Accepted Answer

Long range forecasts in sales dollars are typically used by top management in decision making, such as strategic planning and resource allocation. Managers at the operations level are more focused on short-term goals and day-to-day operations, so these forecasts may not be as relevant to their work.

Question 10

All time series contain random variation but may not contain trend or seasonal components.

Accepted Answer

Random variation, also known as noise or residual variation, refers to the unpredictable fluctuations in a time series that cannot be explained by any identifiable trend or seasonal pattern. Therefore, it is possible for a time series to contain only random variation without any trend or seasonal components.

Question 11

Statistical forecasting is based upon the assumption that the future will be an extrapolation of the past.

Accepted Answer

Statistical forecasting relies on historical data to predict future trends and events, operating on the assumption that patterns of the past will continue into the future.

Question 12

Aggregate forecasts are generally much easier to develop whereas detailed forecasts require more time and resources.

Accepted Answer

This statement is true. Aggregate forecasts involve predicting overall trends and patterns for a large group or market segment, while detailed forecasts involve predicting specific quantities or values for individual items or events. As a result, aggregate forecasts can often be developed more quickly and with fewer resources than detailed forecasts.

Question 13

A single moving average is most appropriate for data with identifiable trends.

Accepted Answer

A single moving average is better suited for smoothing data and identifying the direction of the trend, but it does not well adapt to data with changing trends or seasonal patterns. For data with identifiable trends, more sophisticated methods like exponential smoothing or ARIMA models are often more appropriate.

Question 14

MAD, MSE, and MAPE forecast error metrics generally give similar numerical results so it doesn't matter which one is used.

Accepted Answer

MAD, MSE, and MAPE are three different forecast error metrics that each have their own strengths and weaknesses. While they may produce similar numerical results in certain cases, they are not interchangeable and should be chosen based on the specific needs of the forecasting project.

Question 15

Exponential smoothing models "never forget" past data as long as the smoothing constant is strictly between 0 and 1. In contrast, moving average methods "completely forget" all data older than k periods in the past.

Accepted Answer

Exponential smoothing models give more weight to recent data, but still consider past data. On the other hand, moving average methods only consider a fixed number of past periods and completely ignore older data.

Question 16

Another name for planning horizon is time bucket.

Accepted Answer

The answer of Another name for planning horizon is time...

Question 17

In an exponential smoothing model, larger values of alpha i.e., closer to 1) place less emphasis on recent data and more on older data.

Accepted Answer

Larger values of alpha place more emphasis on recent data and less on older data. Smaller values of alpha, closer to 0, place more emphasis on older data and less on recent data.

Question 18

Trends are characterized by repeatable periods of ups and downs over short periods of time.

Accepted Answer

Trends refer to general directions in which something is developing or changing over longer periods, not short-term fluctuations.

Question 19

Seasonal patterns can occur over the weeks during a month, over days during a week, or hours during a day.

Accepted Answer

Seasonal patterns can occur at different time scales, including weekly, daily, and hourly patterns.

Question 20

Because of random variations, forecasts are never 100% accurate.

Accepted Answer

Random variations and unexpected events can impact the accuracy of any forecast, making it impossible to be 100% accurate.

Quiz 11: Forecasting and Demand Planning