ISQS Final Exam

a. trend

For a time series, its systematic pattern of decline or growth is characterized as its _______. a. trend b. bias c. planning horizon d. forecast error

c. More than 15 but less than or equal to 20 The MAD for the forecasts shown in the given table is more than 15 but less than or equal to 20. MAD is simply the average of the sum of the absolute deviations for all the forecast errors. M A D space equals space fraction numerator sum space vertical line space A subscript t space minus space F subscript t space vertical line over denominator T end fraction where At is the observed value of the time series and Ft is the forecast. Therefore, MAD = 80/5 = 16.

What is the mean absolute deviation (MAD) for the forecasts in the provided table? Month Forecast Demand Actual Demand April 190 200 May 175 185 June 190 220 July 240 230 August 260 240 a. More than 10 but less than or equal to 15 b. More than 25 but less than or equal to 30 c. More than 15 but less than or equal to 20 d. More than 20 but less than or equal to 25

c. The forecast error in month 4 is more than 15. The forecast error in month 4 is more than 15. A moving average forecast is an average of the most recent "k" observations in a time series. Thus, the forecast for the next period (t + 1), which we denote as Ft+1, for a time series with t observations is Ft+1 = sum left parenthesis o f space m o s t space r e c e n t space k space o b s e r v a t i o n s right parenthesis divided by k 3-month moving average for month 4 (F4) = (88 + 102 +125)/3= 105 Therefore, the forecast in month 4 is 105. The forecast error in month 4 = Sales in month 4 - Forecast for month 4 = 122 - 105 = 17.

Use the table of tube sock sales provided below to determine the forecast error in month 4 using a 3-month moving average. Assume each column's data are that of consecutive months. Month 1 2 3 4 Sales 88 102 125 122 a. The forecast error in month 4 is more than 10 but less than or equal to 15. b. The forecast error in month 4 is less than or equal to 5. c. The forecast error in month 4 is more than 15. d. The forecast error in month 4 is more than 5 but less than or equal to 10.

a. More than 15 percent The MAPE for the forecasts shown in the given table is more than 10 percent but less than or equal to 15 percent. MAPE is simply the average of the percentage error for each forecast value in the time series. Therefore, MAPE = (0+4+25+30+18.75)/5 = 15.55.

Use the table provided to solve this problem. What is the mean absolute percentage error (MAPE) for the forecasts provided? Month Forecast Demand Actual Demand April 100 100 May 120 125 June 150 200 July 140 200 August 130 160 a. More than 15 percent b. More than 10 percent but less than or equal to 15 percent c. Less than or equal to 5 percent d. More than 5 percent but less than or equal to 10 percent

a. bias

A tracking signal offers the means to monitor a forecast by numerically representing _______. a. bias b. validity c. throughput d. probability

d. a survey questionnaire

A typical approach used to collect data for judgmental forecasts is _______. a. regression analysis b. single exponential smoothing c. a moving average model d. a survey questionnaire

b. bias

As it pertains to forecasting, _______ references a forecast's tendency to be larger or smaller than the actual values of a time series on a consistent basis. a. variability b. bias c. trend d. fad

c. Single exponential smoothing

Choose the forecasting technique used for forecasting the time series value in a subsequent period by employing a weighted average of previous time-series values. A moving average forecast b. A grassroots forecast c. Single exponential smoothing d. Regression analysis

b. Values of the smoothing constant larger than 0.5 place more emphasis on recent data.

Choose the most accurate statement regarding simple exponential smoothing. Assume the time series is relatively stable with minimal random variability. a. Typical values for the smoothing constant are in the range of 1 to 1.5. b. Values of the smoothing constant larger than 0.5 place more emphasis on recent data. c. Exponential smoothing models completely forget past data if the smoothing constant is strictly between 0 and 1. d. Values of the smoothing constant smaller than 0.1 allow a forecast to react faster to changing conditions.

d. Planning a firm's initial public offering

Consider the functional area of accounting and finance. Which of the following is an example of a project that belongs to that area? a. Annual performance and compensation review b. Market research study c. Installing a revenue management system d. Planning a firm's initial public offering

d. 5 Given the equation, the value of the intercept of the straight line that best fits the time series is 3. A linear function is represented as Yt = a + bt, where Yt represents the estimate of the energy cost in year t, a represents the intercept, and b represents the slope of the straight line that best fits the time series. The energy costs of YingYang, Inc. related to time by a linear function Yt = 5 + 3t. Therefore, the intercept of the straight line that best fits the time series is 5.

Harry, an executive manager at YingYang Inc., plotted the company's energy costs of $1 billion over the last 10 years. His chart implied the energy costs were increasing linearly and predictably. Further, the energy costs were dependent on time by the function, Y t = 5 + 3t. Y t represents the yearly energy cost in year t. Based on this linear equation, what is the value of the intercept that best fits the time series. a. 3 b. 1 c. 10 d. 5

b. Crashing a project

Jim Halpert has less time to finish a project because of the antics of his boss, Michael Scott. Which term describes reducing the time allowable to complete a project in order to meet a revised due date? a. Project resource leveling b. Crashing a project c. Benchmarking d. Activity sequencing

b. Seasonal patterns

Of the choices provided, which can be defined as repeatable periods of ups and downs over relatively short periods of time, as it pertains to data patterns and variations in a time series? a. Cyclical patterns b. Seasonal patterns c. Random variations d. Irregular variations

c. Statistical forecasting

Select the forecast or method that is rooted in the assumption future outcomes will be an extrapolation of previous observations. a. Judgmental forecasting b. The Delphi method c. Statistical forecasting d. The Cooke method

a. It increases the total cost of the project.

Suppose you were to crash a project. Which statement below is most accurate about your action? a. It increases the total cost of the project. b. It is a trade-off between project revenue and additional input costs. c. It increases the total time taken to complete the project. d. It involves the removal of resources from selected project activities to reduce cost.

a. Path A-F-G-H is the critical path.

The district magistrate of Arkham City has decided to rebuild the busiest road in the city. She plans to close the street for the duration of the work, causing immense inconvenience to the people who typically use the road. The project has 3 parallel paths defined as the following: Path A-B-C-H will take 16 days. Path A-D-E-H will take 22 days. Path A-F-G-H will take 30 days. Given the information on hand, which of the following statements is true? a. Path A-F-G-H is the critical path. b. Path A-D-E-H has the largest slack time. c. The expected duration of the project is 68 days. d. Activities B, D, and F have an earliest starting time of 0.

b. The forecast for sales in year 6 is more than 2000 but less than or equal to 2200. The forecast for sales in year 6 is more than 2000 but less than or equal to 2200. Forecast for sales in year 6 is (Y6) = 580 + 260(6) = 2140. Excel provides a very simple tool to find the best-fitting regression model for a time series.

The sales data for high-end staplers at an office store called Staplers are provided in the following table for the previous 5 years. After management plotted this data on a chart, it became clear the sales were predictably increasing in a linear manner. Further, the sales were dependent on time by the function, Y t = 580 + 260t. Compute the forecasted sales in year 6 by utilizing simple linear regression. Year Sales 1 950 2 1050 3 1200 4 1650 5 1950 a. The forecast for sales in year 6 is more than 1800 but less than or equal to 2000. b. The forecast for sales in year 6 is more than 2000 but less than or equal to 2200. c. The forecast for sales in year 6 is more than 2400 but less than or equal to 2600. d. The forecast for sales in year 6 is more than 2200 but less than or equal to 2400.

c. The sales forecast for July is more than 35 but less than or equal to 40. The sales forecast for July is more than 35 but less than or equal to 40. The basic exponential smoothing model is Ft+1 =αAt +(1 - α)Ft = Ft+ α(At- Ft), where At is the observed value of the time series, Ft is the forecast, and α is the smoothing constant (0 ≤ α ≤ 1). FJune = FMay+ α(AMay - FMay) = 32.25 + 0.40(40 - 32.25) = 35.35 FJuly = FJune+ α(AJune - FJune) = 35.35 + 0.40(42 - 35.35) = 38.01 Therefore, the sales forecast for July is 38.01.

The table below illustrates the sales data for a specific model of a Blu-ray player. Assuming the forecast sales for May is 32.25, determine the sales forecast for July by applying a simple exponential smoothing (SES) model. Assume the value of the smoothing constant is 0.40. Month Sales Jan 35 Feb 29 Mar 39 Apr 42 May 40 Jun 42 a. The sales forecast for July is more than 40 but less than or equal to 45. b. The sales forecast for July is more than 45 but less than or equal to 50. c. The sales forecast for July is more than 35 but less than or equal to 40. d. The sales forecast for July is more than 30 but less than or equal to 35.

d. More than 0.30 An exponential smoothing model must have a smoothing constant of more than 0.30 to be roughly equivalent to a moving average model with a seven-month moving average. The smoothing constant is approximately related to the value of kin the moving average model by the following relationship: α = 2/(k + 1), where α is the smoothing constant and k is the most recent observations in a time series. Therefore, α = 2/(k + 1) = 2/(4 + 1) = 0.40.

What should the value of the smoothing constant (α) be in an exponential smoothing model to be generally equivalent to a moving average model that has employed a 4-month moving average? a. Less than or equal to 0.20 b. More than 0.25 but less than or equal to 0.30 c. More than 0.20 but less than or equal to 0.25 d. More than 0.30

b. Judgmental forecasting

What technique is used to predict future demands when historical data is unavailable? a. Regression analysis b. Judgmental forecasting c. Exponential smoothing d. Statistical forecasting

a. Demand is relatively stable and consistent.

When are moving average (MA) methods most effective? a. Demand is relatively stable and consistent. b. A cyclical pattern is observed in a time series. c. There is a major trend in a time series. d. A long planning horizon is involved.

c. forecast will overshoot the actual values

When the time series in an exponential smoothing model produces a negative trend, the _______. a. mean square error will be negative b. value of smoothing constant will either be less than zero or greater than one c. forecast will overshoot the actual values d. future forecasts will rely solely upon expertise of people in developing forecasts

b. Regression analysis

Which method is used in the construction of a statistical model that establishes a relationship between one or more independent, numeric variables and one dependent, numeric variable? a. The Delphi method b. Regression analysis c. Judgmental forecasting d. The Cooke method

a. Short-range forecasts

Which of the following are instrumental in the planning of production schedules and the assignment of workers to jobs by operations managers? a. Short-range forecasts b. Credit scorecards c. Intermediate-range forecasts d. Balanced scorecards

a. Intermediate-range forecasts

Which of the options has the most utility for allocating budgets among divisions, scheduling jobs and resources, and planning workforce levels? a. Intermediate-range forecasts b. Short-range forecasts c. Make-to-stock operations d. Make-to-order operations

d. Long-range forecasts

Which of the options provided are associated with the effective planning of facility expansion? a. Intermediate-range forecasts b. Make-to-stock operations c. Make-to-order operations d. Long-range forecasts

c. Forecast error

Which term describes the value achieved by subtracting the forecast value from the observed value in a time series? a. Forecast consumption b. Forecast density c. Forecast error d. Forecast precision

b. Irregular variation

With data patterns in a time series in mind, which term describes an explainable, one-time variation? a. Cyclical variation b. Irregular variation c. Seasonal variation d. Random variation

c. Cyclical patterns

With time series data patterns in mind, which type of pattern can be described as regular upturns and downturns in a data series which occur over long periods of time? a. Orthographic patterns b. Seasonal patterns c. Cyclical patterns d. Parallel patterns