slide 1 dsci 5340: predictive modeling and business forecasting spring 2013 – dr. nick...
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![Page 1: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/1.jpg)
slide 1
DSCI 5340: Predictive Modeling and Business Forecasting
Spring 2013 – Dr. Nick Evangelopoulos
Exam 1 review: Quizzes 1-6
![Page 2: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/2.jpg)
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POP QUIZ #1
1. The regression sum of squares (SSR) can never be greater than the total sum of squares (SST).
A. TRUE
B. FALSE
√
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POP QUIZ #1
2. The value of the t-test for testing b1 = 0 gives the same value as the t-test for testing that correlation r =0:
A. TRUE
B. FALSE
√
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POP QUIZ #1
3. How can a confidence interval for the true slope β1 be used to test if β1 is equal to 0?
A. If the C.I. includes zero, β1 is not 0
B. If the C.I. does not include zero, β1 is probably 0
C. If the C.I. includes zero, β1 is probably 0√
![Page 5: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/5.jpg)
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POP QUIZ #1
4. Does the residual plot shown below violate any of the model assumptions?
A. No, the plot is symmetric
B. No, the plot is random
C. Yes, the plot is not bell-shaped
D. Yes, the plot shows a non-random pattern
√
![Page 6: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/6.jpg)
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POP QUIZ #1
5. For small data sets, an observation is called an outlier if its studentized residual is:
A. Greater than 0
B. Greater than 2
C. Less than 0
D. Less than 2
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![Page 7: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/7.jpg)
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POP QUIZ #2
1. The value of the test statistic to test if the slopes of the regression model for males and females are the same is :
A: 3.04 B: 2.56 C: 0.82 D: -1.65
![Page 8: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/8.jpg)
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POP QUIZ #2
2. The regression equation for males (Gender=1) is :
A: salary = 42235.42 + 1659.63EDUCAT -1034.14EXPER
B: salaries = 42235.42 + 1659.63EDUCAT + 16.68EXPER
C: salaries = 42235.42 + 625.49EDUCAT + 16.68EXPER
![Page 9: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/9.jpg)
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POP QUIZ #31. Cyclical variation:
A. describes a gradual cyclical movement about the trend
B. is generally attributable to business and economic conditions
C. has its cycle length measured from one peak to the next
D. All of the above
![Page 10: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/10.jpg)
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POP QUIZ #32. The model below is called:
A. Additive Model
B. Multiplicative Model
C. Component Model
D. None of the above
ttttt ICSTRy
![Page 11: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/11.jpg)
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POP QUIZ #33. In the deseasonalized multiplicative model below, how
can we isolate the cyclical activity?
A. By dividing yt by the trend estimate yt-hat
B. By dividing yt by the seasonal component St
C. By dividing yt by the cyclical component Ct
D. By dividing yt by the irregular component It
tttt ICTRy
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POP QUIZ #34. In the four-step procedure for Time Series
Decomposition, what is the recommended first step?
A. Determine the trend component
B. Determine the irregular component
C. Determine the seasonal indices
D. Determine the forecasted values
ttttt ICSTRy
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POP QUIZ #35. In a Time Series Decomposition model, which
components are the most useful in estimating future values?
A. The cyclical and irregular components
B. The seasonal, cyclical, and irregular components
C. The trend and seasonal components
D. The trend, cyclical, and irregular components
ttttt ICSTRy
![Page 14: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/14.jpg)
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POP QUIZ #41. Exponential Smoothing is a forecasting method
that is most effective when the trend and seasonal components of the time series are changing over time:
A. TRUE
B. FALSE
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POP QUIZ #42. In Exponential Smoothing, recent and remote
observations are weighted:
A. Equally
B. Unequally
![Page 16: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/16.jpg)
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POP QUIZ #43. Holt’s trend corrected exponential smoothing method
applies to time series data that have
A. A local linear trend that changes slowly
B. A global linear trend that remains constant
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POP QUIZ #51. Estimation in classical Box-Jenkins models is
done using ordinary least squares (OLS):
A. TRUE
B. FALSE
![Page 18: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/18.jpg)
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POP QUIZ #52. Box-Jenkins models are seasonal:
A. TRUE
B. FALSE
![Page 19: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/19.jpg)
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POP QUIZ #53. Can classical Box-Jenkins models
accommodate nonstationary time series data?A. Yes, because they can be transformed to
stationary through differencing
B. Yes, because they can be transformed to stationary through a log-transformation
C. No, one should never use Box-Jenkins models when the data is nonstationary
![Page 20: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/20.jpg)
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POP QUIZ #54. ARIMA stands for:
A. Autoregressive Integrated Mean Approximation
B. Autoregressive Integrated Moving Average
C. Autoregressive Indicators for Moving Average
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POP QUIZ #55. Stationarity is defined as the property where:
A. Statistical properties remain constant over time
B. Statistical properties evolve slowly over time
C. Statistical properties change fast over time
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POP QUIZ #61. What happens to the mean and variance of an
AR(1) model if the 1 coefficient is equal to 1?
A. Mean and variance drift to zero
B. Mean and variance drift to infinity
C. The mean drifts to zero, the variance drifts to infinity
D. The mean drifts to infinity, the variance drifts to zero
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![Page 23: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/23.jpg)
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POP QUIZ #62. What is the name of the function that identifies
the order of an autoregressive B-J model?
A. Polynomial function
B. Autoregressive function
C. Moving Average function
D. Characteristic function√
![Page 24: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/24.jpg)
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POP QUIZ #63. Is the model yt = yt-1 + at stationary or
nonstationary? Why?A. Nonstationary, because it has a unit root
B. Stationary, because it has a unit root
C. Nonstationary, because it does not have a unit root
D. Stationary, because it does not have a unit root
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![Page 25: Slide 1 DSCI 5340: Predictive Modeling and Business Forecasting Spring 2013 – Dr. Nick Evangelopoulos Exam 1 review: Quizzes 1-6](https://reader036.vdocuments.us/reader036/viewer/2022062407/56649c755503460f94929453/html5/thumbnails/25.jpg)
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POP QUIZ #64. The “X” in ARIMAX stands for:
A. Extra
B. Previous
C. Exogenous
D. Exotic
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POP QUIZ #65. Based on the SCAN output below, a tentative
ARIMA model seems to be:
A. MA(0)
B. AR(0)
C. MA(1)
D. AR(1)
√