Chapter 8 (*)

Suppose that you want to set up a 3-month weighted moving average forecasting system. You want the weights to be percentages (that add to 100%). Furthermore, you want weights for the most recent two months to be equal but you want each of those weights to be twice as large as the weight for the oldest month. What should the weight be for the oldest month? a) 33% b) 25% c) 80% d) 50% e) 20%

e

Which of the following is the least useful sales forecasting model to use when sales are increasing? a) Trend adjusted exponential smoothing b) Simple mean c) Exponential smoothing d) Weighted moving average e) Naïve

b

Which of the following is true with respect to the correlation coefficient r? a) r2 ≤ r b) r2 ≤ | r | c) r2 ≥ r d) r2 ≥ | r | e) r2 can never equal r

b

Suppose that you are using the naïve forecasting method with trend to forecast sales. If sales have been declining by 20% per week, and this week's sales amounted to $200, what would your forecast be for next week? a) $200 b) $ 40 c) $240 d. $180 e) $160

e

The OM supervisor informs you, the researcher, that the data has a large standard deviation. What data pattern would you expect to observe once you generated a time series trend? a) horizontal b) seasonal c) positive/negative trend d) cycle e) insufficient information to derive a valid response

e

The following correlation coefficient values come from five different linear regression models. Which model "fits" the data the best? a) 0.99 b) 0.5 c) 0 d) −0.8 e) −1

e

What is a tracking signal used for? a) To identify trends in actual data b) To identify seasonality in actual data c) To identify the effect of business cycles on actual data d) To compute the value of the smoothing constant, α, for exponential smoothing e) To identify forecast bias

e

What is the statistic that measures the direction and strength of the linear relationship between two variables? a) r2 b) Coefficient of variation c) Variance d) Coefficient of kurtosis e) Correlation coefficient

e

Which is typically the most difficult data pattern to predict? a) Horizontal b) Trend c) Level d) Seasonality e) Cycle

e

Which of the following is a causal forecasting method? a) Naïve b) Moving average c) Weighted moving average d) Trend adjusted exponential smoothing e) Linear regression

e

The first step in forecasting is: a) determine what data is available b) decide what to forecast c) evaluate and analyze appropriate data d) select and test the forecast model e) establish the forecast accuracy requirements

b

In exponential smoothing, which of the following values for α would generate the most stable forecast? a) 0.10 b) 0.25 c) 0.50 d) 0.75 e) 1.00

a

Over the long term, which of the following forecasting models will likely require carrying the least amount of data? a) Naïve b) Simple mean c) Exponential smoothing d) Weighted moving average e) Moving average

a

Suppose that you are interested in trend-adjusted exponential smoothing. Which of the following values of the trend smoothing constant, β, would most likely be seen in practice? a) 0.10 b) 0.50 c) 0.75 d) 0.90 e) 1.00

a

Suppose that you are using the four-period simple moving average method to forecast sales, and sales have been increasing by 20% every period. How will your forecasts perform? a) Forecasts will be lower than actual. b) Forecasts will be higher than actual. c) Forecasts will equal actual. d) Forecasts will be decreasing. e) Forecasts will be increasing by 5.0% every period

a

Suppose that you are using the four-period simple moving average method to forecast sales, and sales have been increasing by 40% every period. How will your forecasts perform? a) Forecasts will be increasing by 40.0% every period. b) Forecasts will be higher than actual. c) Forecasts will equal actual. d) Forecasts will be decreasing. e) Forecasts will be increasing by 10.0% every period.

a

Suppose that you are using the simple mean to make a forecast. This period's forecast was equal to 100 units, and it was based on 6 periods of demand. This period's actual demand was 86 units. What is your forecast for next period? a) 98 b) 100 c) 93 d) 86 e) Not enough information is given to answer the question.

a

Suppose that you are using the simple mean to make a forecast. This period's forecast was equal to 200 units, and it was based on 5 periods of demand. This period's actual demand was 300 units. What is your forecast for next period? a) 217 b) 250 c) 260 d) 300 e) 200

a

Which forecasting method is particularly good for determining customer preferences? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

a

Which of the following forecasting methods would be most accurate if demand were rapidly decreasing? a) 3-month moving average b) 6-month moving average c) 12-month moving average d) Simple mean e) Exponential smoothing with α = 0.001

a

Which of the following is not a feature common to all forecasting models? a) This period's forecast error is needed to compute next period's forecast. b) Forecasts are rarely perfect. c) Forecasts are more accurate for groups of items rather than for individual items. d) Forecasts are more accurate for shorter rather than for longer time horizons. e) All of the answer choices are correct.

a

Which of the following is the simplest forecasting method? a) Naïve b) Moving average c) Weighted moving average d) Trend adjusted exponential smoothing e) Linear regression

a

Which of the following values of the correlation coefficient implies that the value of the dependent variable decreases as the value of the independent variable increases? a) −0.2 b) 0 c) 0.2 d) 1 e) 0.5

a

____________________ is a collaborative process between two trading partners that establishes formal guidelines for joint forecasting and planning. a) Collaborative Planning Forecasting and Replenishment (CPFR) b) Supply Chain Planning Forecasting and Replenishment (SCPFR) c) Supply Chain Optimization (SCO) d) Collaborative Creation of Guidelines (CCG) e) Joint Planning and Forecasting (JPP)

a

Under which forecasting method does a group of managers meet to generate a forecast? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

b

What value of the correlation coefficient implies that there is no relationship between the two variables of a linear regression model? a) −1 b) 0 c) 0.5 d) 1 e) ∞

b

Which forecasting method suffers from the possibility of having one person's opinion dominate the forecast? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

b

Which of the following forecasting methods is most likely to be implemented to change an existing quantitative forecast to account for a new competitor in the marketplace? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

b

Which of the following is not a step in Forecasting Seasonality? a) Calculate a seasonal index for each season of each year b) Divide this year's average seasonal demand by each average seasonal index c) Average the indexes by season d) Forecast demand for the next year and divide by the number of seasons e) Calculate the average demand per season

b

A firm has the following order history over the last 6 months. January 120 February 95 March 100 April 75 May 100 June 50 What would be a 3-month weighted moving average forecast for July, using weights of 40% for the most recent month, 30% for the month preceding the most recent month, and 30% for the month preceding that one? a) 75 b) 72.5 c) 50 d) 90 e) 106.5

b

In linear regression, an r2 of .984 implies what? a) 98.4% of the variability of the independent variable is explained by the dependent variable b) 98.4% of the variability of the dependent variable is explained by the independent variable c) 1.6% of the variability of the independent variable is explained by the dependent variable d) 1.6% of the variability of the dependent variable is explained by the independent variable e) 99.2% of the variability of the dependent variable is explained by the independent variable

b

In linear regression, what are we trying to forecast? a) Beta parameter b) Dependent variable c) Independent variable d) Y-intercept of the line e) Slope of the line

b

Qualitative forecasting methods a) are made objectively by the forecaster b) are made subjectively by the forecaster c) are made using existing data sources d) are based on mathematical models e) are only used in parallel with quantitative models

b

Suppose that you are using the exponential smoothing forecasting method, and this period's forecast (Ft) was 100% accurate (i.e., no error). If α = .5, which of the following is definitely true? a) Next period's forecast will also be 100% accurate. b) Next period's forecast equals this period's actual. c) This period's forecast must be thrown out, and next period's forecast equals Ft-1 + α (At-1 α − Ft-1). d) Next period's forecast equals 50% of this period's forecast. e) Next period's forecast equals 50% more than this period's forecast

b

Suppose that you are using the four-period simple moving average method to forecast sales, and sales have been decreasing by 10% every period. How will your forecasts perform? a) Forecasts will be lower than actual. b) Forecasts will be higher than actual. c) Forecasts will equal actual. d) Forecasts will be increasing. e) Forecasts will be decreasing by 2.5% every period

b

Suppose that you are using the simple mean to make a forecast. This period's forecast was equal to 1000 units, and it was based on 99 periods of demand. This period's actual demand was 0 units. What is your forecast for next period? a) 1000 b) 990 c) 0 d) 1010 e) 999

b

A causal research model is based on the assumption that a) the independent variable is related to the dependent variable b) there is a relationship between the time series and the dependent variable c) the variable being forecast is related to other variables in the environment d) there is a relationship between the time series and the independent variable e) the information is contained in a time series of data

c

Consider the demand data listed below. What is the 4-month moving average forecast for June? Month Actual Demand Jan. 10,000 Feb. 12,000 Mar. 24,000 Apr. 8,000 May 14,000 a) 14,000 b) Not enough information is given to answer the question. c) 14,500 d) 13,500 e) 15,333

c

Forecasting is not a function which contributes to: a) deciding which business market to pursue b) deciding which product to produce c) deciding how bonuses should be allocated d) deciding how much inventory to carry e) deciding how many people to hire

c

Suppose that Jane's company uses exponential smoothing to make forecasts. Further suppose that last period's demand forecast was for 500 units and last period's actual demand was 480 units. In addition, yesterday Jane found out that this period's actual demand will be for 550 units. Jane's company uses an α value of .20. Today, Jane's boss asked her to prepare a forecast for this period. What should that forecast be? a) 504 b) 496 c) 510 d) 484 e) 550

c

Suppose that you are using the four-period weighted moving average forecasting method to forecast sales and you know that sales will be increasing every period for the foreseeable future. What of the following would be the best set of weights to use (listed in order from the most recent period to four periods ago, respectively)? a) 0.25, 0.25, 0.25, 0.25 b) 0.40, 0.30, 0.20, 0.10 c) 1.00, 0.00, 0.00, 0.00 d) 0.10, 0.20, 0.30, 0.40 e) 0.00, 0.00, 0.00, 1.00

c

Suppose that you are using the naïve forecasting method with trend to forecast sales. If sales have been increasing by 40% per month, and this month's sales amounted to $1200, what would your forecast be for next month? a) $1200 b) $ 480 c) $1680 d) $ 720 e) $1600

c

What are the most frequently used forecasting techniques? a) Linear regression b) Simple mean c) Exponential smoothing d) Weighted moving average e) Econometric models

c

What does the linear regression line do? a) Minimizes sum of errors b) Minimizes product of squared errors c) Minimizes sum of squared errors d) Minimizes product of errors e) Minimizes sum of absolute value of errors

c

When is exponential smoothing equivalent to the "naïve" approach to forecasting? a) When the smoothing constant is chosen randomly b) α = 0 c) α = 1 d) α = .5 e) When next month's forecast equals this month's forecast

c

Which forecasting method is particularly good for predicting technological changes and scientific advances? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

c

Which forecasting method seeks to develop a consensus among a group of experts? a) Market research b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

c

Which of the following companies helps businesses use weather data to make their business plans? a) i2 technologies b) Manugistics c) Planalytics d) Algorithmics e) SAP

c

Which of the following forecasting methods is specifically designed to go through several rounds of modification before generating a final forecast? a) Exponential smoothing b) Executive opinion c) Delphi method d) Naïve method e) Gamma method

c

Which of the following is not considered to be one of the four basic patterns of time series data? a) Horizontal b) Trend c) Vertical d) Seasonality e) Cycle

c

"Inside information" is most likely garnered through which of the following forecasting methods? a) exponential smoothing b) seasonal indexes c) naïve d) Delphi e) multiple regression

d

A firm has had the following order history over the last 4 months: November 140 December 80 January 100 February 150 What is the weighted moving average forecast for March, assuming a weight of 60% for the most recent month, 30% for the month preceding the most recent month, and 10% for the month preceding that one? a) 117.5 b) 228.1 c) 118.0 d) 128.0 e) 132.4

d

In exponential smoothing, what values can the smoothing constant, α, have? a) [−1, 1] b) [1, ∞] c) [0, ∞] d) [0, 1] e) [−∞, ∞]

d

In looking at seasonal indexes one weakness to watch for is a) use of the wrong alpha b) incorrect selection of weights c) a clear lack of linear relationship d) seasonality is not present e) significant increase in computational requirements

d

One quantitative forecasting models limitation is a) it is objective b) they are consistent c) they are based on mathematical formulas d) they are limited on the quality of available data e) they can work around bad data

d

Suppose that Sally's company uses exponential smoothing to make forecasts. Further suppose that last period's demand forecast was for 20,000 units and last period's actual demand was 21,000 units. Sally's company uses a smoothing constant (α) equal to 40%. What should be the forecast for this period? a) 20,000 b) 21,000 c) 20,600 d) 20,400 e) 19,600

d

Suppose that you are using the naïve forecasting method with trend to forecast sales. Sales have been increasing by 10% per week. Two weeks ago, sales amounted to $100. What should your forecast be for this week? a) $100 b) $ 10 c) $110 d) $121 e) $120

d

The following sales figures show actual sales over the identified time period. What can be determined by comparing a simple mean forecast and a six month moving average forecast? December 4,000 January 5,000 February 4,000 March 4,500 April 5,500 May 5,000 a) moving average develops a smoother forecast b) 4.7, 5 c) 4.7, 4 d) 4, 4 e) 4, 4.7

d

What are the two categories of quantitative models? a) Delphi and non-causal b) Causal and non-causal c) Delphi and time series d) Causal and time series e) Causal and Delphi

d

What value of the correlation coefficient implies that there is a perfect positive linear relationship between the two variables of a linear regression model? a) −1 b) 0 c) 0.5 d) 1 e) ∞

d

When evaluating forecasting models it is accurate to say: a) they all rely on the same data sets b) they will provide the same results c) they are usually accurate d) they differ in their degree of complexity e) they do not differ in their degree of complexity

d

Which forecasting method assumes that next period's forecast is equal to this period's actual value? a) Simple mean b) Ignorant c) Basic d) Naïve e) Nescient

d

Which of the following is not one of the nine steps utilized in the most complete form of CPFR? a) identify exceptions for order forecasts b) create a sales forecast c) create order forecast d) create separate business plans e) generate order

d

Which of the following is not typically done jointly by CPFR trading partners? a) set forecasts b) plan production c) replenish inventories d) raise capital e) evaluate their success in the marketplace

d

Which of the following would not be a consideration for selecting a forecasting software package? a) How easy is the package to learn? b) Is it possible to implement new methods? c) Do you require repetitive forecasting? d) Does the supplier support a local conference? e) Is there any local support?

d

Combined forecasting involves a rule that a) you must work with different vendors b) you need different forecasters c) you must always use a quantitative and qualitative method d) the results are not comparable to a single forecast e) the forecasting methods should be different

e

Given the following data, use exponential smoothing (α = .1) to develop a demand forecast for period 3. Assume the forecast for the initial period is 500. What is the forecast? Period Demand 1 600 2 200 a) 569 b) 470 c) 541 d) 551 e) 479

e

Given the following data, use exponential smoothing (α = .2) to develop a demand forecast for period 3. Assume the forecast for the initial period is 5. What is the forecast? Period Demand 1 7 2 9 a) 9.00 b) 3.72 c) 9.48 d) 5.00 e) 6.12

e

Suppose that you are using exponential smoothing with α = 0.5 and your initial forecast 5 months ago was for 100 units. If the actual demand last month was 0 units, which of the following is definitely true? a) The forecast for this month should be 0. b) The model blew up. You can't use exponential smoothing anymore. c) The forecast for last month was 0. d) The forecast for this month should be 50. e) We need more information to determine this month's forecast.

e