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.

Online MCQs about Time Series Data Analysis and Forecasting

1. Three are __________ main components of a time series.

 
 
 
 

2. The method of least squares to fit in the trend is applicable only if the trend is __________.

 
 
 
 

3. If a straight line is fitted to the time series, then

 
 
 
 

4. A time series data is a set of data recorded at

 
 
 
 

5. The systematic components of a time series which follow regular pattern of variations are called

 
 
 
 

6. Which of the following is an example of irregular variation?

 
 
 
 

7. The forecasts on the basis of a time series are ______________

 
 
 
 

8. A time series consists of __________

 
 
 
 

9. What is the primary objective of differencing in time-series transformation?

 
 
 
 

10. What is the key objective of decomposing a time series in time-series analysis?

 
 
 
 

11. What is the purpose of log transformation in time-series analysis?

 
 
 
 

12. What technique is commonly used for handling seasonality in time-series feature engineering?

 
 
 
 

13. The time series analysis helps:

 
 
 
 

14. The sequence which follows an irregular or random pattern of variation is called _______.

 
 
 
 

15. What is autocorrelation in time-series analysis?

 
 
 
 

16. The component of a time series attached to long-term variations is termed as __________

 
 
 
 

17. The sales of a shopkeeper are associated with the component of a time series

 
 
 
 

18. In time-series analysis, what does “T” typically represent?

 
 
 
 

19. The secular trend is indicative of long-term variation towards

 
 
 
 

20. The linear trend of a time series indicates towards ____________.

 
 
 
 

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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Important MCQs Index Numbers 1

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The post is about MCQs index numbers. There are 20 multiple-choice questions related to the basics of index numbers, price relative, fixed base method, chain base methods, weighted index numbers, Paasche’s index numbers, Laspeyrs index numbers, and Fisher Idea index numbers. Let us start with the MCQs Index Numbers Quiz.

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MCQs Index Numbers

MCQs Index Numbers
  • The index number that can be used for multi-purpose is:
  • An index number computed for a single commodity is called
  • The ———- index number has a wide scope
  • The price relative formula is $\frac{?}{P0}\times 100$
  • The index for the base period is always taken as
  • In the fixed base method, the base period should be
  • The commodities subject to considerable price variations can be best measured by
  • In the chain base method, the base period is
  • The chaining process used to make a comparison of the index number is
  • Price relatives computed for the chain base method are called
  • The most suitable average for index numbers is
  • Index numbers are free from a unit of measurement because the index number shows
  • Long-term variations are regarded as
  • Paasche’s price index number is also called
  • The index number having an upward bias is
  • The index give by $\frac{\sum p_n q_n}{\sum p_0 q_0}\times 100$
  • If Laspeyre’s index number is 200, and Paasche’s index number is 200 then the Fisher index number will be
  • Increased demand for coolers in summer and heaters in winter is an example of
  • The price used in the construction of consumer price index numbers is
  • ——— method uses quantities consumed in the base period when computing a weighted index
MCQs Index Numbers

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Important MCQ Random Variables 1

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 The post is about MCQ Random Variables. There are 20 multiple-choice questions related to random experiments, random variables and types of random variables, expectations, discrete random variables, and continuous random variables. Let us start with the MCQ Random Variables Quiz.

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MCQ Random Variables Quiz

MCQ Random Variables Quiz
  •  If $X$ is a continuous random variable, then function $f(X)$ is
  • A variable (Random Variable) assuming an infinite number of values is called
  • A variable whose value is determined by the outcome of a random experiment is called
  • If $X$ and $Y$ are random variable then $E(X + Y)$ is equal to
  • If $X$ is a discrete random variable, the function $f(X)$ is
  • When four coins are tossed, the value of a random variable (Numbers of head) is
  • A variable (Random Variable) assuming a finite number of values is called
  • If $X$ and $Y$ are independent random variables then $E(XY)$ is equal to
  • Two random variables $X$ and $Y$ are said to be independent if:
  • If $X$ and $Y$ are two independent variables, then
  • A continuous random variable is a random variable that can
  • If $X$ is a random variable that can take only non-negative values, then
  • For a random variable $X$, $E(X)$ is
  • If $C$ is a non-random variable, the $E(C)$ is
  • A continuous variable is a variable that can assume
  • A ———– random variable has a countable number of possible values.
  • Which of the following statements accurately describes a key difference between discrete and continuous random variables?
  • Which of the following are examples of discrete random variables?
  • Which of the following statements describes continuous random variables?
  • If $X$ is a random variable and $a$ and $b$ are constants then $Var(aX+ b)$ is equal to
MCQ Random Variables

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Important MCQs Probability Distributions 4

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The post is about MCQs Probability Distributions. There are 20 multiple-choice questions covering the topics related to Chi-Square distribution, F-distribution, Binomial distribution, Student’s t distribution, and properties of distributions. Let us start with MCQs Probability Distributions.

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MCQs Probability Distributions Quiz

MCQs Probability Distributions with Answers
  • A family of parametric distribution in which mean always greater than its variance is:
  • The family of parametric distributions which has a mean always less than variance is:
  • The family of parametric distributions for which moment generating function does not exist is:
  • The distribution for which the mode does not exist is:
  • The relation between the mean and variance of $\chi^2$ with $n$ degrees of freedom is
  • The $F$-distribution curve in respect of tails is:
  • If $X$ has a binomial distribution with parameter $p$ and $n$ then $\frac{X}{n}$ has the variance:
  • The binomial distribution is symmetrical if $p=p=?$
  • The shape of geometric distribution is
  • If $X\sim N(\mu, \sigma^2)$ and $a$ and $b$ are real numbers, then mean of $(aX+b)$ is
  • The distribution of sample correlation is
  • Events having an equal chance of occurrence are called
  • Student’s $t$-distribution curve is symmetrical about mean, it means that
  • The distribution possessing the memoryless property is
  • The chi-square distribution is used for the test of
  • The probability of failure in binomial distribution is denoted by
  • In binomial distribution, the formula for calculating the mean is  
  • In binomial probability distribution, dependents of standard deviations must include
  • The formula to calculate standardized normal random variables is
  • The mean of a binomial probability distribution is 857.6 and the probability is 64% then the number of values of binomial distribution
Statistics MCQS Probability Distributions Quiz

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