University of Cincinnati

BANA 2082

Quiz 8A

1)The company identified in Chapter 8, Analytics in Action, is _______________

2. The Analytics in Action example in Chapter 8 concerned

3. Chapter 8 focuses on

4. A forecast is defined as a(n)

5. A set of observations on a variable measured at successive points in time or over successive periods of time constitute a

6. Which of the following is not present in a time series?  

Quiz 15 & 8

1. Three decision makers have assessed payoffs for the following decision problem (payoff in dollars).

For each of the cases, assume that the utilities for best and worst payoffs are 10 and 0, respectively.

If P(s1) = 0.30, P(s2) = 0.55, and P(s3) = 0.15, find a recommended decision for Decision Maker

A. What is the expected value of this decision? Round you answer to two decimal places?

2. Consider Question 1, and determine the answer for Decision Maker B.

3. Consider Question 1, and determine the answer for Decision Maker C.

4. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of losing $3000? Round your answer to three decimal places.

5. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of losing $1500? Round your answer to three decimal places.

6. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of a zero payoff? Round your answer to three decimal places.

7. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of earning $1500? Round your answer to three decimal places.

8. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of earning $3000? Round your answer to three decimal places.

9. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of earning $4500? Round your answer to three decimal places.

10. Translate the following monetary payoffs into utilities for a decision maker whose utility function

is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of earning $6000? Round your answer to three decimal places.

11. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of earning $7500? Round your answer to three decimal places.

12. Translate the following monetary payoffs into utilities for a decision maker whose utility function is described by an exponential function with R = 6450: –$3000, –$1500, $0, $1500, $3000,

$4500, $6000, $7500, $9000.

What is the utility of earning $9000? Round your answer to three decimal places.

13. A time series plot of a period of time (in months) verses sales (in number of units) is shown below. Which of the following data patterns best describes the scenario shown?

14. A time series plot of a period of time (in weeks) verses sales (in 1,000’s of gallons) is shown below. Which of the following data patterns best describes the scenario shown?

15. A time series plot of a period of time (in years) verses revenue (in millions of dollars) is shown below .Which of the following data patterns best describes the scenario shown?

16. A time series plot of a period of time (in years) verses sales (in thousands of dollars) is shown below Which of the following data patterns best describes the scenario shown?

17. A time series plot of a period of time period (quarterly) verses quarterly sales (in $1,000s) is shown below. Which of the following data patterns best describes the scenario shown?

18. Consider the following quarterly time series.

Construct a time series plot. What type of pattern exists in the data?

19. Consider the following time series data.

Construct a time series plot. What type of pattern exists in the data?

Quiz 8B

1. Forecast error

2. The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast.These methods measure forecast accuracy by

3. A positive forecast error indicates that the forecasting method                the dependent variable.

4. Which of the following measures of forecast accuracy is susceptible to the problem of positive and negative forecast errors offsetting one another?

5. Suppose for a particular week, the forecasted sales were $4,000. The actual sales were $3,000. What is the value of the mean absolute percentage error?

6. The moving averages method refers to a forecasting method that

7.                                                        uses a weighted average of past time series values as the forecast.

Quiz 8C

1. A time series with a seasonal pattern can be modeled by treating the season as a

2. Autoregressive models

3. The value of an independent variable from the prior period is referred to as a

4. Causal models

5. A causal model provides evidence of                                   between an independent variable and the variable to be forecast.
6. For causal modeling,                                       are used to detect linear or nonlinear relationships between the independent and dependent variables.

Quiz 8D

1. 
   Consider the following time series data.

Develop a three-year moving average for this time series. Determine the MSE. Round your answer to two decimal places.

2. 
   Consider the following time series data.

Develop a three-year moving average for this time series. What is your forecast for period 11? Round your answer to two decimal places.

3. Consider the following time series data.

Use α = 0.2 to compute the exponential smoothing values for the time series. Determine the MSE. Round your answer to two decimal places.

4. 
   Consider the following time series data.

Use α = 0.2 to compute the exponential smoothing values for the time series. What is your forecast for Period 11? Round your answer to two decimal places.

5. The below time series gives the indices of Industrial Production in U.S for 10 consecutive years.