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Time Series Analysis Multiple Choice Questions and Answers | Time Series Analysis MCQs Quiz

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Free download in PDF Time Series Analysis Multiple Choice Questions and Answers for competitive exams. These short objective type questions with answers are very important for Board exams as well as competitive exams like UPSC, NDA, SSC etc. These short solved questions or quizzes are provided by Gkseries./p>

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(1) In autoregressive models _______ ?
[A] Current value of dependent variable is influenced by current values of independent variables
[B] Current value of dependent variable is influenced by current and past values of independent variables
[C] Current value of dependent variable is influenced by past values of both dependent and independent variables
[D] None of the above
Answer: Current value of dependent variable is influenced by past values of both dependent and independent variables
(2) Which of the following is true for white noise?
[A] Mean =0
[B] Zero autocovariances
[C] Zero autocovariances except at lag zero
[D] Quadratic Variance
Answer: Zero autocovariances except at lag zero

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(3) For the following MA (3) process yt = μ + Εt + θ1Εt-1 + θ2Εt-2 + θ3Εt-3 , where σt is a zero mean white noise process with variance σ2
[A] ACF = 0 at lag 3
[B] ACF =0 at lag 5
[C] ACF =1 at lag 1
[D] ACF =0 at lag 2
Answer: ACF =0 at lag 5
(4) The pacf (partial autocorrelation function) is necessary for distinguishing between ______ ?
[A] An AR and MA model is_solution: False
[B] An AR and an ARMA is_solution: True
[C] An MA and an ARMA is_solution: False
[D] Different models from within the ARMA family
Answer: An AR and an ARMA is_solution: True
(5) Second differencing in time series can help to eliminate which trend?
[A] Quadratic Trend
[B] Linear Trend
[C] Both A & B
[D] None of the above
Answer: Quadratic Trend
(6) Which of the following cross validation techniques is better suited for time series data?
[A] k-Fold Cross Validation
[B] Leave-one-out Cross Validation
[C] Stratified Shuffle Split Cross Validation
[D] Forward Chaining Cross Validation
Answer: Forward Chaining Cross Validation
(7) Find 95% prediction intervals for the predictions of temperature in 1999.

These results summarize the fit of a simple exponential smooth to the time series.

[A] 0.3297 2 * 0.1125
[B] 0.3297 2 * 0.121
[C] 0.3297 2 * 0.129n
[D] 0.3297 2 * 0.22
Answer: 0.3297 2 * 0.121
(8) Which of the following statement is correct?

1. If autoregressive parameter (p) in an ARIMA model is 1, it means that there is no auto-correlation in the series.

2. If moving average component (q) in an ARIMA model is 1, it means that there is auto-correlation in the series with lag 1.

3. If integrated component (d) in an ARIMA model is 0, it means that the series is not stationary.

[A] Only 1
[B] Both 1 and 2
[C] Only 2
[D] All of the statements
Answer: Only 2
(9) In a time-series forecasting problem, if the seasonal indices for quarters 1, 2, and 3 are 0.80, 0.90, and 0.95 respectively. What can you say about the seasonal index of quarter 4?
[A] It will be less than 1
[B] It will be greater than 1
[C] It will be equal to 1
[D] Seasonality does not exist
Answer: It will be greater than 1
(10) A common method known as ratio-to-trend analysis used to
[A] Deseasonalize data
[B] Take moving average
[C] Remove multicollinearity
[D] Represent graphical curve
Answer: Deseasonalize data

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