Deck 9: Forecasting

Question 1

Describe three qualitative forecasting techniques and compare their strengths and weaknesses.

Answer 1

Answers may vary as the text presents five such methods; market surveys, panel consensus forecasting, the Delphi method, the life cycle analogy method, and build-up forecasts. Market surveys are structured questionnaires submitted to potential consumers, often to gauge potential demand. The surveys can be expensive and time consuming but if structured well and properly administered and interpreted, can be very effective.
Panel consensus forecasting is a technique that brings experts together to jointly discuss and develop a forecast. The Delphi method is a technique where experts work individually to develop forecasts that are subsequently shared among the group, after which each participant is allowed to modify his forecast based upon the other group members' ideas. This is an iterative process that is repeated until consensus is reached. Both methods are expensive and time consuming but can be quite accurate if done correctly. Panel consensus allows for immediate feedback and group synergy. While Delphi lacks immediate feedback and synergy inherent in group discussion, it avoids the problem of a dominant group member.
The life cycle analogy method attempts to identify time frames and demand levels for the introduction, growth, maturity, and decline life cycle stages of a new product or service.
The build-up forecast method sums the specific market forecasts of individuals familiar with those segments.

Question 2

The panel consensus forecasting approach requires that the forecasting team discuss their forecast as a team but the ________ requires that each member of the team develop a separate forecast initially.

Answer 2

Delphi method

Question 3

Forecasts are almost always wrong.

Answer 3

True

Question 4

A counseling service records the number of calls to their hotline for the last year. use this table to answer the following questions:
$$\begin{array} { | l | c | } \hline { \text { Month } } & \text { Demand } \\\hline \text { Tanuary } & 111 \\\hline \text { February } & 127 \\\hline \text { March } & 146 \\\hline \text { April } & 159 \\\hline \text { May } & 165 \\\hline \text { fune } & 165 \\\hline \text { fuly } & 178 \\\hline \text { August } & 182 \\\hline \text { September } & 191 \\\hline \text { October } & 208 \\\hline \text { November } & 223 \\\hline \text { December } & 228 \\\hline\end{array}$$

-What is the forecast for October if a weighted moving average with weights of 0.5, 0.3, and 0.2 is used to model this data?

A)177.4
B)185.7
C)197.7
D)190.3

Question 5

A drive-in restaurant has experienced the following customer loads on the past 8 Friday nights. If their forecast for period 7 was 59 customers, then what is their forecast for period number 8 using a smoothing constant of 0.7? $$\begin{array} { | c | c | } \hline \text { Friday } & \text { \# Customers } \\\hline 1 & 49 \\\hline 2 & 55 \\\hline 3 & 57 \\\hline 4 & 59 \\\hline 5 & 56 \\\hline 6 & 61 \\\hline 7 & 62 \\\hline 8 & 63 \\\hline\end{array}$$

A)61.10
B)62.43
C)59.90
D)60.83

Question 6

A counseling service records the number of calls to their hotline for the last year. use this table to answer the following questions:
$$\begin{array} { | l | c | } \hline { \text { Month } } & \text { Demand } \\\hline \text { Tanuary } & 111 \\\hline \text { February } & 127 \\\hline \text { March } & 146 \\\hline \text { April } & 159 \\\hline \text { May } & 165 \\\hline \text { fune } & 165 \\\hline \text { fuly } & 178 \\\hline \text { August } & 182 \\\hline \text { September } & 191 \\\hline \text { October } & 208 \\\hline \text { November } & 223 \\\hline \text { December } & 228 \\\hline\end{array}$$

-What is the forecast for July if the service uses a simple moving average of three periods?

A)169
B)163
C)157
D)178

Question 7

Qualitative forecasts are used when there is plenty of relevant data.

Question 8

Fed up with her working conditions at the call center, Lisa decides to invest in a state-of-the-art sewing machine and produce limited quantities of her own clothing designs. After a few months of operation, she decides to apply some of the forecasting techniques she mastered in school. Which of these statements about her forecasts is correct?

A)Her forecasts will probably be 100% accurate.
B)Her demand forecasts for a year from now will probably be more accurate than her demand forecasts for three months from now.
C)Her demand forecasts for each style of skirt will be more accurate than her demand forecasts for all skirts.
D)The best way for her to determine the amount of fabric she needs is to forecast it based on her customer orders for each type of skirt.

Question 9

A counseling service records the number of calls to their hotline for the last year. use this table to answer the following questions:
$$\begin{array} { | l | c | } \hline { \text { Month } } & \text { Demand } \\\hline \text { Tanuary } & 111 \\\hline \text { February } & 127 \\\hline \text { March } & 146 \\\hline \text { April } & 159 \\\hline \text { May } & 165 \\\hline \text { fune } & 165 \\\hline \text { fuly } & 178 \\\hline \text { August } & 182 \\\hline \text { September } & 191 \\\hline \text { October } & 208 \\\hline \text { November } & 223 \\\hline \text { December } & 228 \\\hline\end{array}$$

-What is the forecast for August if a regression equation is used to model this data?

A)188.3
B)179.9
C)180.6
D)175.7

Question 10

A video game publishing company needs to predict the total sales in the European market for the next year. This is an example of a(n):

A)firm-level demand forecast.
B)overall market demand forecast.
C)supply forecast.
D)price forecast.

Question 11

A qualitative forecasting technique well-suited for demand forecasts of a new product or service is the:

A)Delphi method.
B)build-up forecast.
C)life cycle analogy method.
D)patronage survey.

Question 12

A qualitative forecasting technique in which individuals familiar with specific market segments estimate the demand within these sectors that are then summed to get an overall forecast is called a:

A)market survey.
B)life cycle analogy.
C)panel consensus forecasting.
D)build-up forecast.

Question 13

Heidi favors using a two period moving average but Tim is "an exponential-smoothing man." Tim's demand forecast for May was identical to Heidi's. What value of alpha would Tim need to use in order for his June forecast to be identical to Heidi's if each sticks with their preferred technique? Note that Tim's forecast for May was identical to Heidi's two-period moving average for May. $$\begin{array} { | c | c | } \hline \text { Month } & \text { Demand } \\\hline \text { January } & 154 \\\hline \text { February } & 148 \\\hline \text { March } & 214 \\\hline \text { April } & 180 \\\hline \text { May } & 225 \\\hline \text { June } & 246 \\\hline\end{array}$$

A).085
B).196
C).237
D).348

Question 14

What are the laws of forecasting and what are their implications for operations and supply chain managers?

Question 15

A firm's demand data from the last two quarters is displayed in the table. Use a three period weighted moving average with W_t = 0.7, W_t-1 = 0.2, and W_t-2 = 0.1 to forecast demand for July. $$\begin{array} { | c | c | } \hline \text { Month } & \text { Demand } \\\hline \text { January } & 154 \\\hline \text { February } & 148 \\\hline \text { March } & 214 \\\hline \text { April } & 180 \\\hline \text { May } & 225 \\\hline \text { June } & 246 \\\hline\end{array}$$

A)235.2
B)195.6
C)158.8
D)180.4

Question 16

A long-term movement up or down in a time series is called:

A)seasonality.
B)trend.
C)randomness.
D)cycle.

Question 17

A counseling service records the number of calls to their hotline for the last year. use this table to answer the following questions:
$$\begin{array} { | l | c | } \hline { \text { Month } } & \text { Demand } \\\hline \text { Tanuary } & 111 \\\hline \text { February } & 127 \\\hline \text { March } & 146 \\\hline \text { April } & 159 \\\hline \text { May } & 165 \\\hline \text { fune } & 165 \\\hline \text { fuly } & 178 \\\hline \text { August } & 182 \\\hline \text { September } & 191 \\\hline \text { October } & 208 \\\hline \text { November } & 223 \\\hline \text { December } & 228 \\\hline\end{array}$$

-What is the forecast for March if an adjusted exponential smoothing model is used with ?=0.8 and ?=0.7? The unadjusted forecast for January is 123.5.

A)135.44
B)138.53
C)129.76
D)144.34

Question 18

A firm's demand data from the last two quarters is displayed in the table. Use a three period moving average to forecast demand for July. $$\begin{array} { | c | c | } \hline \text { Month } & \text { Demand } \\\hline \text { January } & 154 \\\hline \text { February } & 148 \\\hline \text { March } & 214 \\\hline \text { April } & 180 \\\hline \text { May } & 225 \\\hline \text { June } & 246 \\\hline\end{array}$$

A)206
B)217
C)223
D)226

Question 19

A counseling service records the number of calls to their hotline for the last year. use this table to answer the following questions:
$$\begin{array} { | l | c | } \hline { \text { Month } } & \text { Demand } \\\hline \text { Tanuary } & 111 \\\hline \text { February } & 127 \\\hline \text { March } & 146 \\\hline \text { April } & 159 \\\hline \text { May } & 165 \\\hline \text { fune } & 165 \\\hline \text { fuly } & 178 \\\hline \text { August } & 182 \\\hline \text { September } & 191 \\\hline \text { October } & 208 \\\hline \text { November } & 223 \\\hline \text { December } & 228 \\\hline\end{array}$$

-What is the forecast for August if the forecast for June was 164 and the service uses exponential smoothing with an alpha of 0.8?

A)164.80
B)188.93
C)180.67
D)175.36

Question 20

The Delphi method, panel consensus forecasting, and market surveys are all qualitative forecasting methods, but only market surveys do NOT use experts.

Question 21

Two time series techniques that are appropriate when the data display a strong upward or downward trend are ________ and ________.

Question 22

Consider the data that generate this plot covering time for months numbered 1 to 50. What characteristic is most prominent in the pattern?

A)trend
B)seasonality
C)randomness
D)none

Question 23

Fluctuations in demand due to seasonality are greater than those due to randomness.

Question 24

Exponential smoothing with an alpha of one will yield identical results to a last period forecast.

Question 25

A(n)________ forecasting model bases all forecasts on past actual values all the way back to the first period.

Question 26

Examine these two graphs and based on the demand pattern and axis scaling, recommend a forecasting technique (and the required parameters)that would work best for each one. Justify your recommendations.

Question 27

The greater the randomness in the data, the ________ the value of the alpha should be in an exponential smoothing forecast.

Question 28

The slope of the regression equation is positive if the r-squared value is greater than 0.0.

Question 29

When there is a significant upward or downward trend in the data, the two of the best forecasting models to use are adjusted exponential smoothing and linear regression.

Question 30

A seasonal pattern in time series data is evident when the level of the variable of interest moves erratically up or down from one period to the next.

Question 31

A seasonal index less than 1.0 means that the model is overforecasted.

Question 32

Dividing actual demand by the model's forecast yields an index that can be used to adjust for ________ in the data.

Question 33

________ is unpredictable movement from one time period to the next.

Question 34

A company keeps track of unit sales and notes a strong trend during the past eight periods. They use an adjusted exponential smoothing model with an alpha equal to 0.7 and a beta equal to 0.6. Using the demand data and previous forecasts shown in the table, develop a forecast for period 4. $$\begin{array} { | c | c | c | c | c | } \hline \text { Week } & \text { \# Units } & \begin{array} { c } \text { Unadjusted } \\\text { Forecast }\end{array} & \text { Trend } & \begin{array} { c } \text { Adjusted } \\\text { Forecast }\end{array} \\\hline 1 & 68 & 65.0 & 0.0 & 65.0 \\\hline 2 & 72 & 67.1 & 1.3 & 68.4 \\\hline 3 & 80 & & & \\\hline 4 & 93 & & & \\\hline 5 & 108 & & & \\\hline 6 & 121 & & & \\\hline 7 & 125 & & & \\\hline 8 & 139 & & & \\\hline\end{array}$$

A)82.2
B)84.9
C)87.5
D)91.6

Question 35

What patterns are common in time series data? Describe each one and draw one plot that displays all of these patterns. Label the patterns on your plot.

Question 36

"A simple moving average was good enough for my dad, and it's good enough for me," Ethan declared as he prepared his forecast. The assistant dean knew that the size of incoming MBA classes had been increasing dramatically over the previous few semesters and that the forecasts Ethan would prepare using his father's method would ________ the actual size of the incoming class.

Question 37

The greater the randomness in the model, the greater the number of periods that should be used in a moving average forecast.

Question 38

Two smoothing models that yield identical forecasts are exponential smoothing with an alpha equal to ________ and a moving average with n equal to ________.

Question 39

Develop forecasts for periods 7 through 10 for the demand data in the table using a three period moving average, a weighted moving average using 0.6, 0.3, and 0.1, and exponential smoothing with alpha = 0.7. Use a 6^th period forecast of 135 as the starting point for the exponential smoothing technique.

Question 40

The independent variable is the quantity the forecaster is interested in estimating with a linear regression model.

Question 41

McMahon and Tate advertising company is interested in an appropriate mix of print, radio, and television ads for their new client. Darrin Stevens performs a multiple regression on the effects of dollars spent on each type of media on dollars of sales of product. Darrin uses data from the most recent advertising campaigns and develops the following equation: y = 254,215 + 6.79 × Print - 1.4 × Radio + 16.87 × Television
The r-squared statistic is 0.77 and all coefficients are significant. Which of the following statements is best?

A)At a minimum, the client will sell $254,215 worth of product after the new advertising campaign.
B)At a maximum, the client will sell $254,215 worth of product after the new advertising campaign.
C)This equation will be of no use in predicting the amount of sales based on advertising in these media.
D)The client should spend more money on television advertising than on radio advertising.

Question 42

A poultry farmer that dabbles in statistics is interested in exploring the relationship between two types of feed (layer pellets and scratch), water, and the output of his laying hens. For ten days he records the number of ounces of layer pellets and scratch the hens consume and the number of fluid ounces of water and tracks the number of eggs that are produced. After running a multiple regression model, he obtains the following report. What is the best interpretation of these statistics? $$\begin{array} { | l | c | c | c | c | } \hline & \text { Coefficients } & \text { Std Error } & t \text { Stat } & P \text {-value } \\\hline \text { Intercept } & 1.256 & 1.249 & 1.006 & 0.353 \\\hline \text { Scratch } & 0.185 & 0.032 & 5.714 & 0.001 \\\hline \text { Layer Pellets } & 0.295 & 0.026 & 11.539 & 0.000 \\\hline \text { Water } & 0.149 & 0.041 & 3.587 & 0.012 \\\hline\end{array}$$

A)For every egg produced, about 0.185 ounces of scratch must be consumed.
B)The standard error for the model intercept is as large as the coefficient, thus the intercept is the most important predictor of egg production.
C)Layer pellets are not good predictors of egg production because the p-value is 0.
D)For every ounce of water consumed, the chickens produce 0.15 eggs, holding all other independent variables constant.

Question 43

Multiple regression was used to forecast success in college (GPA)based upon SAT score, high school GPA, and hours spent on-line. Use the regression output shown and comment on the overall fit of the model, the usefulness of each independent variable, and the value to an admissions department of using the model to make admission decisions. What is the model's forecast for an applicant having a high school GPA of 2.5 and an SAT score of 1000 that spends 20 hours a week on-line? What other variables do you feel would make good indicators of college GPA?

Question 44

A poultry farmer that dabbles in statistics is interested in exploring the relationship between two types of feed (layer pellets and scratch), water, and the output of his laying hens. For ten days he records the number of ounces of layer pellets and scratch the hens consume and the number of fluid ounces of water and tracks the number of eggs that are produced. What is his regression equation based on the data? $$\begin{array} { | c | c | c | c | } \hline \text { Scratch } & \text { Layer Pellets } & \text { Water } & \text { Eggs } \\\hline 48 & 29 & 36 & 24 \\\hline 44 & 27 & 34 & 22 \\\hline 41 & 22 & 31 & 20 \\\hline 42 & 21 & 32 & 20 \\\hline 48 & 23 & 34 & 22 \\\hline 44 & 28 & 34 & 23 \\\hline 42 & 22 & 37 & 21 \\\hline 41 & 28 & 33 & 22 \\\hline 42 & 22 & 31 & 20 \\\hline 47 & 29 & 37 & 24 \\\hline\end{array}$$

A)Eggs = 6.56 + .38Scratch + .17Pellets + .21Water
B)Eggs = 1.25 + .18Scratch + .29Pellets + .15Water
C)Eggs = 0.93 - .88Scratch + .37Pellets + .41Water
D)Eggs = 4.22 + .37Scratch + .67Pellets + .58Water

Question 45

Multiple regression is used when the forecaster believes that more than one independent variable should be used to predict the variable of interest.

Question 46

Using the data in the table, first plot the data and comment on the appearance of the demand pattern. Then develop a forecast for periods 51-70 that fits the data.

Question 47

The ________ value for a regression or multiple regression model shows the percentage of variability in the dependent variable that is explained by the independent variable(s).

Question 48

A poultry farmer that dabbles in statistics is interested in exploring the relationship between two types of feed (layer pellets and scratch), water, and the output of his laying hens. For ten days he records the number of ounces of layer pellets and scratch the hens consume and the number of fluid ounces of water and tracks the number of eggs that are produced. After running a multiple regression model, he obtains the following report. What is the best interpretation of these statistics? Regression Statistics
$$\begin{array} { | l | c | } \hline \text { Multiple R } & 0.993633 \\\hline \text { R Square } & 0.987307 \\\hline \text { Adjusted R Square } & 0.98096 \\\hline \text { Standard Error } & 0.213764 \\\hline \text { Observations } & 10 \\\hline\end{array}$$

A)The probability that the number of eggs is correctly predicted by the amount of scratch, layer pellets, and water consumed is 99.36%.
B)The prediction of the amount of eggs is 98.7% accurate based on the amount of scratch, layer pellets, and water consumed.
C)98.7% of the variability in egg production is explained by the amount of water, scratch, and layer pellets consumed.
D)The prediction of the amount of eggs is 99.36% accurate based on the amount of scratch, layer pellets, and water consumed.

Question 49

As yet another earthquake rattled her china cabinet, the data scientist decided to test whether hydraulic fracturing (where water is injected into the Earth)truly was predictive of the number of earthquakes in the region. What is the slope of the regression equation based on the data? $$\begin{array} { | c | c | } \hline \text { Injections } & \text { Earthquakes } \\\hline 137 & 682 \\\hline 331 & 833 \\\hline 360 & 905 \\\hline 442 & 1008 \\\hline 478 & 1482 \\\hline 529 & 1742 \\\hline\end{array}$$

A)151.24
B)2.52
C)0.85
D)0.72

Question 50

A well-educated lumberjack decides to use linear regression to predict the demand for firewood based on the ambient temperature. He has collected data on firewood sales and temperature for the last several days and has performed some preliminary calculations as shown in the table. What is his regression equation based on the data? $$\begin{array} { | c | c | c | c | c | } \hline & \text { Temp } & \text { Ricks } & \text { Temp Squared } & \text { Temp *\# Ricks } \\\hline & 33 & 17 & 1089 & 561 \\\hline & 19 & 32 & 361 & 608 \\\hline & 34 & 20 & 1156 & 680 \\\hline & 34 & 18 & 1156 & 612 \\\hline & 20 & 33 & 400 & 660 \\\hline & 24 & 30 & 576 & 720 \\\hline & 17 & 34 & 289 & 578 \\\hline & 30 & 25 & 900 & 750 \\\hline & 38 & 16 & 1444 & 608 \\\hline & 23 & 29 & 529 & 667 \\\hline \text { Sums } & 272 & 254 & 7900 & 6444 \\\hline\end{array}$$

A)Ricks = 50.6 - 0.93 × Temp
B)Temp = 53.3 - 1.0 × Ricks
C)Ricks = 0.93 - 50.6 × Temp
D)Temp = 1.0 - 53.3 × Ricks

Question 51

As yet another earthquake rattled her china cabinet, the data scientist decided to test whether hydraulic fracturing (or fracking)truly was predictive of the number of earthquakes in the region. What proportion of the number of earthquakes is predicted by the number of water injections based on the available data? $$\begin{array} { | c | c | } \hline \text { Injections } & \text { Earthquakes } \\\hline 137 & 682 \\\hline 331 & 833 \\\hline 360 & 905 \\\hline 442 & 1008 \\\hline 478 & 1482 \\\hline 529 & 1742 \\\hline\end{array}$$

A)0.96
B)0.89
C)0.85
D)0.72

Question 52

A counseling service records the number of calls to their hotline for the last year. Plot the data and determine which forecasting technique would be best among a moving average, weighted moving average, exponential smoothing, and regression line.

Question 53

Demand was low two years ago but increased sharply last year thanks to an aggressive marketing campaign. A time series model that puts the greatest emphasis on the most recent period is probably the best choice to predict next year's demand.

Question 54

Which of these quantitative techniques can be a causal model?

A)linear regression
B)last period
C)exponential smoothing
D)weighted moving average

Question 55

A poultry farmer that dabbles in statistics is interested in exploring the relationship between layer pellets and the output of his laying hens. For ten days he records the number of ounces of layer pellets and the number of eggs that are produced. What is his regression equation based on the data? $$\begin{array} { | c | c | } \hline \text { Layer Pellets } & \text { Eggs } \\\hline 29 & 24 \\\hline 27 & 22 \\\hline 22 & 20 \\\hline 21 & 20 \\\hline 23 & 22 \\\hline 28 & 23 \\\hline 22 & 21 \\\hline 28 & 22 \\\hline 22 & 20 \\\hline 29 & 24 \\\hline\end{array}$$

A)Eggs = 11.3 + 0.42Pellets
B)Eggs = 1.25 + 0.29Pellets
C)Eggs = 10.9 + 0.23Pellets
D)Eggs = 4.22 + 0.67Pellets

Question 56

A poultry farmer that dabbles in statistics is interested in exploring the relationship between two types of feed (layer pellets and scratch), water, and the output of his laying hens. For ten days he records the number of ounces of layer pellets and scratch the hens consume and the number of fluid ounces of water and tracks the number of eggs that are produced. What is his regression equation based on the data?

Question 57

The Pancake House did a brisk business on the weekend and the maître d' was always on the lookout for ways to improve the customer experience. He carefully tracked the number of customers that graced their establishment over the last four weekends. He was hopeful that he could forecast the number of customers that would come for the world's finest pancakes the next weekend.
Using the data in the table, first plot the data and comment on the appearance of the demand pattern. Then develop a forecast for weekend #5 that fits the data.

Question 58

Heidi runs a multiple regression for the output of cheese curds by using the daily temperature and the consumption of sweet clover. The intercept term is 23, the slope coefficient for the daily temperature is 1.5 and the slope coefficient for the consumption of sweet clover is 0; both coefficients are statistically significant. Which of these conclusions is most appropriate?

A)Heidi should collect more data.
B)The most important term in Heidi's model is the intercept.
C)As the daily temperature rises, the intercept term probably decreases.
D)Heidi should drop the sweet clover term from her model.

Question 59

Using the data shown in the table, develop a regression line that can be used to predict the demand for time period number 20. What is the regression equation and what is your forecast for period 20?

Question 60

Models that predict values based upon some independent factor(s)other than time are ________ forecasting models.

Question 61

As yet another earthquake rattled his china cabinet, the data scientist vowed to once and for all determine whether hydraulic fracturing (where water is injected into the earth)was predictive of the number of earthquakes in the region. Using the data below, develop a regression equation and calculate the MAD and MAPE.

Question 62

The chief meteorologist quit in a huff one afternoon and the station manager turned to a demented walrus to prepare the forecast for the following nine days during sweeps week. The walrus was a ratings hit, but his forecasts, displayed in the table below, were not entirely accurate. Calculate MAD, MAPE and a tracking signal for the forecasts.

Question 63

A counseling service records the number of calls to their hotline for the last year. Based on MAD, which of these models does the best job of forecasting? $$\begin{array} { | l | c | } \hline { \text { Month } } & \text { Demand } \\\hline \text { Tanuary } & 111 \\\hline \text { February } & 127 \\\hline \text { March } & 146 \\\hline \text { April } & 159 \\\hline \text { May } & 165 \\\hline \text { Tune } & 165 \\\hline \text { Tuly } & 178 \\\hline \text { August } & 182 \\\hline \text { September } & 191 \\\hline \text { October } & 208 \\\hline \text { November } & 223 \\\hline \text { December } & 228 \\\hline\end{array}$$

A)a simple moving average of three periods
B)a simple moving average of five periods
C)a weighted moving average of .7, .2, .1
D)a weighted moving average of .5, .2, .2, .1

Question 64

As yet another earthquake rattled his china cabinet, the data scientist vowed to once and for all determine whether hydraulic fracturing (where water is injected into the earth)was predictive of the number of earthquakes in the region. Using the data below, what evidence can you find to support the notion that the number of injections helps explain the number of earthquakes in the region?

Question 65

In order to indicate ________ in a forecast model, you should use the mean forecast error approach rather than the mean absolute deviation approach.

Question 66

Supply chain partners might use ________ to develop joint sales and operations plans and projections of output if they have agreed on a common set of objectives.

Question 67

The tracking signal calculated for the first forecast is always either +1 or -1.

Question 68

Which of these forecasts is the BEST?

A)the one with a MAD of zero
B)the one with the tracking signal of +4
C)the one with the tracking signal of -4
D)the one where the tracking signal times the MAD equals zero

Question 69

As yet another earthquake rattled his china cabinet, the data scientist vowed to once and for all determine whether hydraulic fracturing (or fracking)was predictive of the number of earthquakes in the region. What is the regression equation based on the data?

Question 70

A poultry farmer that dabbles in statistics is interested in exploring the relationship between two types of feed (layer pellets and scratch), water, and the output of his laying hens. For ten days he records the number of ounces of layer pellets and scratch the hens consume and the number of fluid ounces of water and tracks the number of eggs that are produced.
He develops one equation based on three predictors, the scratch, pellets, and water, and another equation based only on the layer pellet consumption. The output for the two models are shown side by side. Comment on the two models and which one should be used.

Question 71

A tracking signal value between ________ and ________ would suggest that the forecasting technique in use is considered to be performing well.

Question 72

A forecaster is assessing two different models for demand. The output from each model and the actual demand data appear in the table. Use MAD and a tracking signal to compare the two models. Which model does a better job of forecasting?

Question 73

Which one of the following statements regarding collaborative planning, forecasting, and replenishment (CPFR)systems is best?

A)In CPFR, each business develops a sales and operations plan and the mainframe system reconciles these plans to find a middle ground that all businesses work towards.
B)CPFR is a set of business processes.
C)CPFR has the Program Management Body of Knowledge (PMBOK©)as its basis.
D)Studies have demonstrated that manual, paper-based CPFR systems are faster and more accurate than computer-based CPFR systems.

Question 74

Nora Damus reviews her forecasting triumphs and failures as part of her annual report to the Chief Operating Officer. She notes that her monthly forecast for batteries has a mean forecast error of 20, and a mean absolute deviation of 20. Which of the following statements about her forecast is BEST?

A)Nora has miscalculated her mean forecast error.
B)Nora has miscalculated her mean absolute deviation.
C)Nora has a negative tracking signal.
D)Nora has a positive tracking signal.

Question 75

A model with a positive mean forecast error suggests that, on average, the model underforecasts.

Question 76

What is a collaborative planning, forecasting, and replenishment system and how might it benefit those who choose to use it?

Question 77

What distinguishes collaborative planning, forecasting, and replenishment (CPFR)systems from traditional planning approaches is the emphasis on forecasting.

Question 78

A collaborative planning, forecasting and replenishment system eliminates the need for forecasting.

Question 79

The forecast data matches the actual data perfectly if the mean absolute deviation is 0.0.