Question 1

Joe's Donut Hole sold 1,500 donuts in January, 1,600 in February, and 1,550 in March. What is the two period simple moving average forecast for April?
A) The two period simple moving average cannot be determined from the information given
B) 1,550
C) 1,600
D) 1,575

Accepted Answer

To calculate the two period simple moving average forecast, we need to take the average of the sales from the two most recent periods.

For April, the two most recent periods are February and March.

So, the two period simple moving average forecast for April would be:

(1,600 + 1,550) / 2 = 1,575

Therefore, the best choice is D.

Question 2

Joe's Donut Hole sold 1,500 donuts in January, 1,600 in February, and 1,550 in March. What is the three period simple moving average forecast for April?
A) The three period simple moving average cannot be determined from the information given
B) 1,550
C) 1,600
D) 1,575

Accepted Answer

The three period simple moving average is calculated by taking the average of the sales from the last three months: (1500 + 1600 + 1550) / 3 = 1550.

Question 3

Joe's Donut Hole sold 1,500 donuts in January, 1,600 in February, and 1,550 in March. What is the four period simple moving average forecast for April?
A) The four period simple moving average cannot be determined from the information given
B) 1,550
C) 1,600
D) 1,575

Accepted Answer

A four period simple moving average requires data from four periods, but only three months of data are provided (January, February, and March). Therefore, the four period simple moving average cannot be determined.

Question 4

The smoothing constant for exponential smoothing must be?
A) Negative
B) Positive
C) Between 0 and 1
D) Greater than 1

Accepted Answer

The smoothing constant for exponential smoothing must be between 0 and 1 to ensure that the weights of previous observations decrease exponentially and that the forecast is based on a weighted average of past observations. A value less than 0 or greater than 1 would lead to unstable forecasts.

Question 5

Exponential smoothing relies on a weighted difference between the current period's _________ and ________.
A) Actual data and the previous period's actual data
B) Actual data and the current period's forecast
C) Actual data and the previous period's forecast
D) Actual data and the next period's actual data

Accepted Answer

Exponential smoothing uses the current period's forecast (which is based on the previous period's actual data and forecast) to weigh in the current period's actual data. Therefore, the weighted difference is between the current period's actual data and the current period's forecast.

Question 6

Unexpected events may lead to demand that is referred to as?
A) Trend
B) Seasonality
C) Cyclical
D) Random variation

Accepted Answer

Random variation refers to unexpected events that cause short-term fluctuations in demand, such as a natural disaster or a sudden change in consumer preferences. Trends, seasonality, and cyclical demand are typically predictable and longer-term patterns in demand.

Question 7

A salesperson has been asked to forecast her sales for the next month. To do so, she decides to average her sales from the past three months. This forecasting technique is referred to as?
A) Simple moving average
B) Weighted moving average
C) Exponential smoothing
D) Linear trend forecast

Accepted Answer

The given scenario describes the use of a simple moving average to forecast sales.

Question 8

A forecasting technique that uses an average of previous observations, with each observation being weighted, is which technique?
A) Simple moving average
B) Linear trend forecast
C) Exponential smoothing
D) Weighted moving average

Accepted Answer

The technique described is a weighted moving average, where each observation is given a different weight. Simple moving average uses equal weights for each observation, linear trend forecast involves fitting a straight line to the data, and exponential smoothing involves giving more weight to recent observations.

Question 9

A forecasting method used when there is a single independent variable (time) and a dependent variable (often demand) and the two variables are linearly related is?
A) Linear trend forecast
B) Simple linear regression forecast
C) Multiple regression forecast
D) Exponential smoothing forecast

Accepted Answer

Linear trend forecast is a forecasting method used when there is a single independent variable (time) and a dependent variable (often demand) and the two variables are linearly related.

Question 10

A model when there are several independent variables that are linearly related to demand is?
A) Linear trend forecast
B) Simple linear regression forecast
C) Multiple regression forecast
D) Exponential smoothing forecast

Accepted Answer

When there are several independent variables that are linearly related to demand, multiple regression forecast is the appropriate model. This model allows for the consideration of multiple factors that may impact demand, unlike simple linear regression which only considers one independent variable. Linear trend forecast and exponential smoothing forecast are appropriate when there is a clear and consistent pattern in past demand data.

Question 11

The simple moving average forecasting technique tends to work well when?
A) Demand rapidly increases then decreases
B) Demand is stable over time
C) Demand is highly variable
D) Demand rapidly decreases then increases

Accepted Answer

The simple moving average forecasting technique works well when demand is stable over time. It is less effective when there are significant changes in demand patterns.

Question 12

Using the average of recent historical demand to generate a forecast is referred to as what technique?
A) Simple moving average
B) Weighted moving average
C) Exponential smoothing
D) Linear trend forecast

Accepted Answer

Simple moving average is a technique where the average of recent historical demand is used to generate a forecast. It is simple to use and requires less computational work compared to other techniques like weighted moving average or exponential smoothing. It is suitable for stable demand patterns and short-term forecasting.

Question 13

A retailer experiencing unexplained variations in sales is likely experiencing?
A) Trend
B) Seasonality
C) Cyclical
D) Random variation

Accepted Answer

Random variation refers to unpredictable and erratic movements in sales that cannot be attributed to any specific pattern or external factors. This can result from a variety of factors such as customer behavior, changes in local economic conditions, or other unexpected events.

Question 14

In the weighted moving average forecast, weights are typically?
A) Descending as data is older
B) Ascending as data is older
C) The same for each period
D) Added to each forecast

Accepted Answer

In the weighted moving average forecast, weights are typically descending as data is older. This is because more recent data is considered to be more relevant and should have a larger impact on the forecast.

Question 15

A causal model that predicts demand when the independent variable and the dependent variable are linearly related is?
A) Linear trend forecast
B) Simple linear regression forecast
C) Multiple regression forecast
D) Exponential smoothing forecast

Accepted Answer

When the independent variable and dependent variable have a linear relationship, the best choice for a causal model to predict demand is a simple linear regression forecast. This model will fit a straight line to the data and use it to make predictions.

Question 16

The weighted moving average forecast tends to?
A) Weight each period equally
B) Weight recent demand more lightly
C) Weight recent demand more heavily
D) Give each period a weight of zero

Accepted Answer

The weighted moving average forecast puts more emphasis on recent demand by assigning higher weights to the most recent data. This is in contrast to a simple moving average forecast, which would give equal weight to all periods.

Question 17

The simple moving average is _______.
A) Able to respond to changes quickly
B) Difficult to calculate for small values of n
C) Not able to respond to changes quickly
D) Insensitive to stable demand

Accepted Answer

The simple moving average is not able to respond to changes quickly, as it gives equal weight to all observations in the time series. It is better suited for smoothing out fluctuations in stable demand. It is not difficult to calculate for small values of n, as it simply takes the mean of the last n observations.

Question 18

In the weighted moving average forecast, weights must?
A) Be non-negative
B) Sum to 1
C) Be non-negative and sum to 1
D) Be neither non-negative nor sum to 1

Accepted Answer

In a weighted moving average forecast, weights must be non-negative to make logical sense since negative weights would imply that the historical data points have a negative influence on the forecast. Additionally, the weights must sum to 1 so that the forecast is a weighted average of the historical data points. Therefore, option C is the correct choice.

Question 19

The simple moving average forecasting technique is?
A) Able to generate consistently perfect forecasts
B) Relatively easy to use
C) Relatively difficult to use
D) Rarely used due to its complexity

Accepted Answer

The simple moving average forecasting technique is relatively easy to use as it involves taking an average of the historical data to predict future values. It is, however, not able to generate consistently perfect forecasts and is not rarely used due to its simplicity.

Question 20

The simple moving average forecast _________.
A) Weights each period equally
B) Weights recent demand more lightly
C) Weights recent demand more heavily
D) Gives each period a weight of zero

Accepted Answer

The simple moving average forecast weights each period equally by taking the average of a set number of previous periods.

Quiz 6: Demand Management, Forecasting, and Aggregate Planning

Joe's Donut Hole sold 1,500 donuts in January, 1,600 in February, and 1,550 in March. What is the two period simple moving average forecast for April?

Joe's Donut Hole sold 1,500 donuts in January, 1,600 in February, and 1,550 in March. What is the three period simple moving average forecast for April?

Joe's Donut Hole sold 1,500 donuts in January, 1,600 in February, and 1,550 in March. What is the four period simple moving average forecast for April?

The smoothing constant for exponential smoothing must be?

Exponential smoothing relies on a weighted difference between the current period's _ and .

Unexpected events may lead to demand that is referred to as?

A salesperson has been asked to forecast her sales for the next month. To do so, she decides to average her sales from the past three months. This forecasting technique is referred to as?

A forecasting technique that uses an average of previous observations, with each observation being weighted, is which technique?

A forecasting method used when there is a single independent variable (time) and a dependent variable (often demand) and the two variables are linearly related is?

A model when there are several independent variables that are linearly related to demand is?

The simple moving average forecasting technique tends to work well when?

Using the average of recent historical demand to generate a forecast is referred to as what technique?

A retailer experiencing unexplained variations in sales is likely experiencing?

In the weighted moving average forecast, weights are typically?

A causal model that predicts demand when the independent variable and the dependent variable are linearly related is?

The weighted moving average forecast tends to?

The simple moving average is _______.

In the weighted moving average forecast, weights must?

The simple moving average forecasting technique is?

The simple moving average forecast _________.