Important Time Series MCQs Test 3

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The post is about Time Series MCQs Quiz. There are 20 multiple-choice questions related to components of time series, additive model for time series, multiplicative models for time series, moving average models, autoregressive models, and mathematical methods for measuring the trend. Let us start with Time Series MCQS.

Online MCQs about Time Series Analysis and Forecasting

1. The most commonly used mathematical method for measuring the trend is

 
 
 
 

2. In the moving average method, we cannot find the trend values of some

 
 
 
 

3. What is the primary purpose of the inverse transformation in time-series analysis?

 
 
 
 

4. Time series data have a total number of components?

 
 
 
 

5. What is the primary purpose of the Moving Average (MA) model in time series analysis?

 
 
 
 

6. What does the term “AutoRegression” mean in the context of time series modeling?

 
 
 
 

7. The multiplicative model for time series is Y = . . .

 
 
 
 

8. In the measurement of the secular trend, the moving averages:

 
 
 
 

9. A fire in a factory delaying production for some weeks is

 
 
 
 

10. A set of observations recorded at an equal interval of time is called

 
 
 
 

11. In the theory of time series, a shortage of certain consumer goods before the annual budget is due to

 
 
 
 

12. Additive model for time series Y = . . .

 
 
 
 

13. A rise in prices before Eid is an example of

 
 
 
 

14. In a Moving Average (MA) model with an order of 3 (MA(3)), how many of the most recent lagged values are used to calculate the forecast for the current time step?

 
 
 
 

15. Seasonal variations are

 
 
 
 

16. The following are the movement(s) in the secular trend

 
 
 
 

17. The graph of time series is called

 
 
 
 

18. Prosperity, Recession, and depression in a business is an example of

 
 
 
 

19. The best-fitted trend line is one for which the sum of squares of residuals or errors is

 
 
 
 
 

20. In an AutoRegression (AR) model with an order of 2 (AR(2)), how many of the most recent lagged values are considered predictors for the current value?

 
 
 
 

Online Time Series MCQs

Time Series MCQs Quiz with answers
  • Additive model for time series Y = . . .
  • The most commonly used mathematical method for measuring the trend is
  • A rise in prices before Eid is an example of
  • Prosperity, Recession, and depression in a business is an example of
  • In the moving average method, we cannot find the trend values of some
  • Seasonal variations are
  • A fire in a factory delaying production for some weeks is
  • The multiplicative model for time series is Y = . . .
  • In the theory of time series, a shortage of certain consumer goods before the annual budget is due to
  • A set of observations recorded at an equal interval of time is called
  • The best-fitted trend line is one for which the sum of squares of residuals or errors is
  • The graph of time series is called
  • In the measurement of the secular trend, the moving averages:
  • The following are the movement(s) in the secular trend
  • Time series data have a total number of components?
  • What is the primary purpose of the inverse transformation in time-series analysis?
  • What does the term “AutoRegression” mean in the context of time series modeling?
  • In an AutoRegression (AR) model with an order of 2 (AR(2)), how many of the most recent lagged values are considered predictors for the current value?
  • In a Moving Average (MA) model with an order of 3 (MA(3)), how many of the most recent lagged values are used to calculate the forecast for the current time step?
  • What is the primary purpose of the Moving Average (MA) model in time series analysis?
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Important MCQs Time Series Quiz 2

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The post is about MCQs Time Series Quiz. There are 20 multiple-choice questions related to components of a time series, multiplicative model of a time series, trend equation, simple average method, and moving average analysis. Let us start with the MCQS Times Series Quiz.

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MCQs Time Series Quiz

Online MCQs Time Series Quiz
  • Irregular variations in a time series are caused by
  • An additive model of a time series with the components $T, S, C$, and $I$ is
  • I multiplicative model of a time series with components $T, S, C,$ and $I$ is
  • A method full of subjectivity to find out the trend line is
  • If the origin in a trend equation is shifted forward by 3 years, $X$ in the equation $Y=a+bx$ will be replaced by:
  • If the origin in the trend equation $Y=a+bx$ is shifted backward by 2 years, the variable $X$ in the trend equation will be replaced by
  • If the trend line with 1995 as the origin is $Y = 20.6 + 1.68 X$, the trend line with origin 1991 is
  • The equation $Y= \alpha \beta^x$ represents
  • The simple average method is used to calculate
  • Irregular variations are
  • A simple average method for finding out seasonal indices is good when
  • The moving average in a time series is free from the influences of:
  • Value of $b$ in the trend line $Y=a+bX$ is
  • A time series consists of
  • For the given five values 15, 24, 18, 33, 42, the three years moving averages are:
  • What is the primary purpose of a seasonal decomposition plot in time series analysis?
  • In time series analysis, what type of plot is commonly used to visualize the autocorrelation of a time series?
  • In time series feature engineering, what is a lag feature?
  • In time series analysis, what is the purpose of scaling features?
  • What is a common approach to handling missing data in time-series analysis?
MCQs Time Series Quiz

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Important MCQs on Experimental Design 1

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The post is about MCQs on Experimental Design with Answers. There are 20 multiple-choice questions. The quiz is related to the Basics of the Design of Experiments, Analysis of variation, assumptions of ANOVA, One-Way ANOVA, Single-factor designs, and Two-Way ANOVA. Let us start with the MCQs on Experimental Design Quiz.

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Online MCQs on Experimental Design

MCQs on Experimental Design Quiz
  • Analysis of variance is used to test
  • The assumption used in ANOVA is
  • In ANOVA we use
  • Consider $k$ independent samples each containing $n_1, n_2, \cdots, n_k$ items such that $n_1+n_2+\cdots+ n_k=n$. In ANOVA we use F-distribution with a degree of freedom
  • In one-way ANOVA, with the usual notation, the error degree of freedom is
  • In one-way ANOVA, given $SSB = 2580, SSE =1656, k = 4, n = 20$ then the value of F is
  • In two-way ANOVA with $m$ rows and $n$ columns, the error degrees of freedom is
  • In one-way ANOVA, the calculated F value is less than the table F value then
  • In two-way ANOVA with $m=5$, $n=4$, then the total degrees of freedom is
  • In one-way ANOVA with the total number of observations is 15 with 5 treatments then the total degrees of freedom is
  • If the treatments consist of all combinations that can be formed from the different factors then the experiment is
  • Consider an experiment to investigate the efficacy of different insecticides in controlling pests and their effects on subsequent yield. What is the best reason for randomly assigning treatment levels (spraying or not spraying) to the experimental units (farms)?
  • Which of the following are important in designing an experiment?
  • Analysis of variance
  • A Mean Square is
  • For a single-factor ANOVA involving five populations, which of the following statements is true about the alternative hypothesis?
  • An experiment is performed in CRD with 10 replications to compare two treatments. The total experimental units will be
  • A teacher uses different teaching ways for different groups in his class to see which yields the best results. In this example a treatment is
  • If the total degrees of freedom between treatments in a CRD are 15 and 4 respectively, the degrees of freedom for error will be
  • If there are 6 treatments with 3 blocks in a RCBD then the degrees of freedom for error are
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Best MCQs Time Series Analysis 1

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The post is about MCQs Time Series Analysis. There are 20 multiple-choice questions related to time series data, components of time series, least square method, objective of times series, differencing time series, decomposing a time series, and log transformation. Let us start with the MCQs time series analysis.

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MCQs Time Series Analysis

MCQs Time Series Analysis
  • A time series data is a set of data recorded at
  • The time series analysis helps:
  • A time series consists of ————.
  • The forecasts on the basis of a time series are ————-.
  • The component of a time series attached to long-term variations is termed as ————.
  • The sales of a shopkeeper are associated with the component of a time series
  • The secular trend is indicative of long-term variation towards
  • The linear trend of a time series indicates towards ———–.
  • The method of least squares to fit in the trend is applicable only if the trend is ————.
  • The sequence which follows an irregular or random pattern of variation is called ————.
  • Three are ———– main components of a time series.
  • The systematic components of a time series which follow regular pattern of variations are called
  • Which of the following is an example of irregular variation?
  • If a straight line is fitted to the time series, then
  • What is autocorrelation in time-series analysis?
  • In time-series analysis, what does “T” typically represent?
  • What is the primary objective of differencing in time-series transformation?
  • What is the purpose of log transformation in time-series analysis?
  • What is the key objective of decomposing a time series in time-series analysis?
  • What technique is commonly used for handling seasonality in time-series feature engineering?
MCQs Time Series Analysis

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