CH 3

Airlines offering low prices for tickets booked months in​ advance, with those ticket prices being higher closer to the travel date is an example​ of: A. complementary products. B. revenue management. C. promotional pricing. D. trend demand pattern.

revenue management.

One aspect of demand that makes every forecast inaccurate​ is: A. trend variation. B. random variation. C. cyclical variation. D. seasonal variation.

random variation.

​Time-series analysis is most effective when used in​ ______-term forecasts. A. long B. medium C. short D. indefinite

short

Data on the weekly sales of room air conditioning units were matched with the average temperature and calculations produced sample correlation​ coefficients, r, in the range of −0.75 and −0.83. Which of the following statements best expresses a conclusion that can be drawn from the values of​ r? A. As the temperature​ increases, the number of room air conditioners sold decreases. B. There is no relationship between temperature and sales. C. This cannot be determined from the information given. D. As the temperature​ decreases, the number of room air conditioners sold decreases.

As the temperature​ increases, the number of room air conditioners sold decreases.

Which one of the following is an example of causal forecasting​ technique? Question content area bottom Part 1 A. Weighted moving average B. Exponential smoothing C. Linear regression D. Delphi method

Linear regression

INCREASING THE SMOOTHING CONSTANT a: A. DECREASES RESPONSIVESNESS B. INCREASES RESPONSIVENESS

DECREASES RESPONSIVESNESS

Aggregating products or services together generally decreases the forecast accuracy. True False

FALSE

Which one of the following statements about forecasting is​ TRUE? A. The five basic patterns of demand are the​ horizontal, trend,​ seasonal, cyclical, and the subjective judgment of forecasters. B. Casual methods are used when historical data are available and the relationship between the factor to be forecast and other external and internal factors cannot be identified. C. Judgment methods are particularly appropriate for situations in which historical data are lacking. D. Focused forecasting is a technique that focuses on one particular component of demand and develops a forecast from it.

Judgment methods are particularly appropriate for situations in which historical data are lacking.

Consider the following data concerning the performance of a forecasting method. MONTH ACTUAL DEMAND FCAST 1 300 270 2 200 280 3 270 260 4 250 270 5 310 250 A. The CFE is greater than​ 100, and the MAD is greater than 50. B. The CFE is greater than​ 100, and the MAD is less than 50. C. The CFE is less than​ 100, and the MAD is less than 50. D. The CFE is less than​ 100, and the MAD is greater than 50.

The CFE is less than​ 100, and the MAD is less than 50.

A linear regression model is developed that has a slope of 5.5 and an intercept of 15. The sample coefficient of determination is 0.75. Which of the following statements is true​? A. The sample correlation coefficient must be 1.00. B. The sample correlation coefficient must be 0.75 C. The sample correlation coefficient must be 0.5625. D. The sample correlation coefficient must be 0.866.

The sample correlation coefficient must be 0.866.

Which one of the following statements about forecasting is​ FALSE? A. Three general types of forecasting techniques are used for demand​ forecasting: time-series​ analysis, causal​ methods, and judgment methods. B. A time series is a list of repeated observations of a​ phenomenon, such as​ demand, arranged in the order in which they actually occurred. C. Time series express the relationship between the factor to be forecast and related factors such as promotional​ campaigns, economic​ conditions, and competitor actions. D. Causal methods of forecasting use historical data on independent variables​ (promotional campaigns,​ competitors' actions,​ etc.) to predict demand.

Time series express the relationship between the factor to be forecast and related factors such as promotional​ campaigns, economic​ conditions, and competitor actions.

A manufacturing firm has developed a skills​ test, the scores from which can be used to predict​ workers' production rating factors. Worker Test_Score Production_Rating Worker Test_Score Production_Rating A 58 45 K 65 59 B 41 47 L 78 77 C 94 89 M 70 57 D 89 79 N 34 28 E 91 84 O 61 51 F 69 76 P 27 27 G 56 49 Q 81 85 H 53 48 R 37 34 I 44 46 S 51 60 J 72 76 T 42 32 Using least​ squares-linear regression​ module, Y=____+____X where Y=Production rating and X=Test score. b. If a​ worker's test score was 42​, what would be your forecast of the​ worker's production​ rating? 4040. c. The coefficient of correlation for the​ least-squares regression model is 0.9430.943 and the coefficient of determination is 0.8890.889. ​ There is a (POSITIVE?NEGATIVE?) relationship. The regression equation explains ____​% of variation in ratings.

Using POM for​ Windows' least​ squares-linear regression​ module, develop a relationship to forecast production ratings from test scores. ​ Y=-0.2581+.9515X where Y=Production rating and X=Test score. b. If a​ worker's test score was 42​, what would be your forecast of the​ worker's production​ rating? 40. c. The coefficient of correlation for the​ least-squares regression model is 0.943 and the coefficient of determination is 0.889 There is a strong positive relationship. The regression equation explains 89​% of variation in ratings.

Which of the following is NOT a principle of the forecasting​ process? A. Better processes yield better forecasts. B. Whenever​ possible, forecast in detail at more disaggregated levels. C. Bias is the worst kind of forecast error. D. The best way to improve forecast accuracy is to focus on reducing forecast error.

Whenever​ possible, forecast in detail at more disaggregated levels.

The materials handling manager of a manufacturing company is trying to forecast the cost of maintenance for the​ company's fleet of​ over-the-road tractors. The manager believes that the cost of maintaining the tractors increases with their age. The following data was​ collected: Observation Age_(years) Yearly_Maintenance_Cost_($) Observation Age_(years) Yearly_Maintenance_Cost_($) 1 6.5 1,219 10 7.0 1,794 2 6.5 1,649 11 2.5 763 3 6.5 1,633 12 2.5 782 4 6.0 1,095 13 7.0 1,364 5 6.0 1,323 14 8.0 1,973 6 6.0 1,281 15 3.0 1,578 7 6.0 1,490 16 3.0 1,066 8 7.0 2,122 17 3.0 1,149 9 7.5 1,587 * * * a. Use POM for​ Windows' least​ squares-linear regression module to develop a relationship to forecast the yearly maintenance cost based on the age of a tractor. ​ Y=____+____X where Y=Yearly maintenance cost in dollars and X=Age in years. b. If a section has 30 two​-year-old ​tractors, what is the forecast for the annual maintenance​ cost? ​$____

Y=608.85+143.8 $26893.80

Quantitative forecasting techniques include A. the Delphi method. B. manager opinions. C. consumer surveys. D. exponential smoothing.

exponential smoothing.

The level of product sales appears to be highly correlated with the money spent on advertising to promote the product. The marketing team wants to create a linear regression model to assist them in forecasting the product demand. In this​ scenario: A. the independent variable is the money spent on advertising. B. the dependent variable is the money spent on advertising. C. the independent variable is product demand. D. there are two dependent variables.

the independent variable is the money spent on advertising.

The Universal Computer company saw a systematic increase in demand for their newly introduced tablet computer. This is an example of​ a: A. random demand pattern. B. seasonal demand pattern. C. cyclical demand pattern. D. trend demand pattern.

trend demand pattern.

A weary traveler shows up at a hotel desk at midnight without a reservation. The desk clerk informs him that there is a room​ available, but sadly it is marked up​ 80% higher than the usual price. This is an example of A. backlogs. B. promotional pricing. C. backorder. D. yield management.

yield management.

Franklin​ Tooling, Inc., manufactures specialty tooling for firms in the​ paper-making industry. All of their products are​ engineer-to-order and so the company never knows exactly what components to purchase for a tool until a customer places an order.​ However, the company believes that weekly demand for a few components is fairly stable. Component 135.AG is one such item. The last 26 weeks of historical use of component 135.AG is recorded below. Week Demand Week Demand 1 127 14 121 2 126 15 122 3 133 16 114 4 116 17 111 5 131 18 117 6 118 19 108 7 139 20 110 8 126 21 105 9 124 22 96 10 132 23 115 11 115 24 103 12 114 25 111 13 108 26 109 Use OM​ Explorer's Time Series Forecasting Solver to evaluate the following forecasting methods. Start error measurement in the fifth​ week, so all methods are evaluated over the same time interval. Use the default settings for initial forecasts. ​(i) Naive​ (1-Period Moving​ Average). The CFE​ (or mean​ bias) is ____ The MAD is ____) The MSE is ____ The MAPE is ____ ​(ii)​ 3-Period Moving Average. The CFE is ____ The MAD is ____ The MSE is ____ The MAPE is ____ ​(iii) Exponential​ smoothing, with α=0.12. The CFE is ____ The MAD is ____ The MSE is _____ The MAPE is ____ ​(iv) Trend projection with Regression. The CFE is ____ The MAD is ____ THE MSE is ____ The MAPE is ____ ​(v) Which forecasting method should management​ use? If CFE is the performance criterion chosen by the​ administration, it should choose the ____ method. If MAD is the performance criterion chosen by the​ administration, it should choose the trend projection with ____ method. If MSE is the performance criterion chosen by the​ administration, it should choose the trend projection with ____ method. If MAPE is the performance criterion chosen by the​ administration, it should choose the trend projection with ____ method.

​(i) Naive​ (1-Period Moving​ Average). The CFE​ (or mean​ bias) is -7.00 The MAD is 8.77 The MSE is 110.95 The MAPE is 7.497% ​(ii)​ 3-Period Moving Average. The CFE is -29.33 The MAD is 6.88 The MSE is 65.59 The MAPE is 5.96%. ​ ​(iii) Exponential​ smoothing, with α=0.12. The CFE is −120.10 The MAD is 7.71 The MSE is 88.50 The MAPE is 6.91​%. ​(iv) Trend projection with Regression. The CFE is 12.32. The MAD is 5.62 THE MSE is 44.32 The MAPE is 4.84 ​(v) Which forecasting method should management​ use? If CFE is the performance criterion chosen by the​ administration, it should choose the naive method. If MAD is the performance criterion chosen by the​ administration, it should choose the trend projection with regression method. If MSE is the performance criterion chosen by the​ administration, it should choose the trend projection with regression method. If MAPE is the performance criterion chosen by the​ administration, it should choose the trend projection with regression method.

In linear​ regression, one​ variable, called a​ __________ variable, is related to one or more​ ____________ variables by a linear equation. A. ​dependent; response B. ​dependent; independent C. ​response; dependent D. ​independent; dependent

​dependent; independent