Online Basic Statistics MCQs 4

The post is about Online Basic Statistics MCQs. There are 20 multiple-choice questions covering topic related to the measure of dispersion, coefficient of v variation, Moments, skewness, kurtosis, distribution of data, and measure of central tendency. Let us start with Online Basic Statistics MCQs with Answers.

Online MCQs Statistics with Answers

1. The Coefficient of Skewness is always zero for ____________ distribution

 
 
 
 

2. In uni-model distribution, if the mode is less than the mean

 
 
 
 

3. The first moment about means is always

 
 
 
 

4. In Mesokurtic distribution

 
 
 
 

5. _________ is used for the criterion of consistency i.e. for consistent performance

 
 
 
 

6. In the plural sense, statistics means

 
 
 
 

7. To compare the variation of two or more than two series, we use ________.

 
 
 
 

8. If $\beta_2=\frac{m_4}{m_2^2}<3$, the distribution is called

 
 
 
 

9. If $\overline{X}=25$, which of the following will be the minimum?

 
 
 
 

10. A lack of symmetry is called

 
 
 
 

11. If the third moment about the mean is zero then the distribution is

 
 
 
 

12. If the right tail is longer than the left tail then distribution is called

 
 
 
 

13. The harmonic mean for any two positive numbers $a$ and $b$ is _______.

 
 
 
 

14. ____________ is used to compare the variation or dispersion in two or more sets of data even though they are measured in different units.

 
 
 
 

15. For the Mesokurtic curve of the distribution, $\beta_2$ is

 
 
 
 
 

16. The Quartile Coefficient of skewness lies between

 
 
 
 

17. The degree of peakedness is called

 
 
 
 

18. Statistics are ______________.

 
 
 
 

19. The second moment about mean is

 
 
 
 

20. If the mean is 25 and the standard deviation is 5 then C.V (Coefficient of variation) is

 
 
 
 

Online Basic Statistics MCQs with Answers

Online Basic Statistics MCQs with Answers
  • If the mean is 25 and the standard deviation is 5 then C.V (Coefficient of variation) is
  • ———– is used to compare the variation or dispersion in two or more sets of data even though they are measured in different units.
  • ———– is used for the criterion of consistency i.e. for consistent performance
  • The first moment about means is always
  • The second moment about mean is
  • If the third moment about the mean is zero then the distribution is
  • The Coefficient of Skewness is always zero for ———— distribution
  • A lack of symmetry is called
  • The Quartile Coefficient of skewness lies between
  • In uni-model distribution, if the mode is less than the mean
  • If the right tail is longer than the left tail then distribution is called
  • The degree of peakedness is called
  • For the Mesokurtic curve of the distribution, $\beta_2$ is
  • If $\beta_2=\frac{m_4}{m_2^2}<3$, the distribution is called
  • In Mesokurtic distribution
  • If $\overline{X}=25$, which of the following will be the minimum?
  • The harmonic mean for any two positive numbers $a$ and $b$ is ————-.
  • To compare the variation of two or more than two series, we use ————.
  • In the plural sense, statistics means
  • Statistics are ————.
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Best MCQs Statistics with Answers 2

The post is about MCQs Statistics with Answers. There are 20 multiple-choice questions covering topics related to the basics of statistics, level of measurements, variables, data, data collection methods, measures of central tendency and dispersion, numerical quantity, sample, population, etc. Let us start with the MCQs Statistics with Answers.

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MCQs Statistics with Answers

MCQs Statistics with Answers
  • In inferential statistics, we study
  • In descriptive statistics, we study
  • When data are collected in a statistical study for only a portion or subset of all elements of interest we are using:
  • In statistics, a sample means
  • The height of a student is 60 inches. This is an example of
  • Data in the Population Census Report is:
  • Which of the following is not based on all the observations?
  • The statistic is a numerical quantity, which is calculated from:
  • Which one of the following measurements does not divide a set of observations into equal parts?
  • Which branch of statistics deals with the techniques that are used to organize, summarize, and present the data:
  • You asked five of your classmates about their height. Based on this information, you stated that the average height of all students in your university or college is 67 inches. This is an example of:
  • In statistics, conducting a survey means
  • The algebraic sum of deviations from the mean is:
  • In statistics, a population consists of:
  • Which one is the not measure of dispersion?
  • If there is no gap between the consecutive classes, the limits are called
  • If all the items in a variable are non-zero and non-negative then ————-.
  • The mean is affected by the change of ————.
  • The data which have NOT undergone any statistical treatments are:
  • If any value in a series is zero then we cannot compute the ————-.
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Important MCQs Probability Questions 1

The post contains MCQs Probability Questions with Answers. There are 20 multiple-choice questions covering topics related to the statistical experiment, basics of probability, sample space, addition rule of probability, multiplication rule of probability, and conditional probability. Let us start with MCQs Probability Questions.

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MCQs Probability Questions with Answers

MCQs probability questions with answers
  • The Complement of $P(A|B)$ is
  • The probability of an intersection of two events is computed by using the
  • If two events $A$ and $B$ are mutually exclusive events, then
  • The range of probability is
  • In a statistical experiment, each time the experiment is repeated
  • The set of all possible outcomes (sample points) is called
  • The sample space (experimental outcomes) refers to
  • An experiment that consists of tossing 4 coins successively. The number of sample points in this experiment is
  • On a December day, the probability of snow is 0.30. The probability of a “cold” day is 0.50. The probability of snow and a “cold” is 0.15. Do snow and “cold” weather are independent events?
  • If $P(A)=0.5$ and $P(B)=0.5$, then $P(A \cap B)$ is
  • If $A$ and $B$ are independent events with $P(A)=0.6$ and $P(B)=0.6$, then $P(A \cap B)=$?
  • If events $A$ and $B$ are independent events with $P(A)=0.2$ and $P(B)=0.6$, then $P(A \cup B)=$?
  • If $A$ and $B$ are independent events with $P(A)=0.4$ and $P(B)=0.25$, then $P(A \cup B)=$?
  • Events $A$ and $B$ are mutually exclusive. Which of the following statements is true?
  • If events $A$ and $B$ are independent events with $P(A)=0.05$ and $P(B)=0.65$, then $P(A|B)=$?
  • A six-sided die is tossed three times. The probability of observing three ones in a row is
  • If $P(A|B)=0.3$
  • If events $A$ and $B$ are independent events with $P(A)=0.1$ and $P(B)=0.4$, then
  • If $P(A|B)=0.3$ and $P(B)=0.8$, then
  • If $P(A)=0.6$, $P(B)=0.3$, and $P(A \cap B)=0.2$, then $P(B|A)=$?
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Best Online Estimation MCQs 1

Online Estimation MCQs for Preparation of PPSC and FPSC Statistics Lecturer Post. There are 20 multiple-choice questions covering the topics related to properties of a good estimation (unbiasedness, efficiency, sufficiency, consistency, and invariance), expectation, point estimate, and interval estimate. Let us start with the Online Estimation MCQs Quiz.

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Online Estimation MCQs with Answers

Online Estimation MCQs with Answers
  • If $Var(\hat{\theta})\rightarrow 0$ as $n \rightarrow 0$, then $\hat{\theta}$ is said to be
  • If $E(\hat{\theta})=\theta$, then $\hat{\theta}$ is said to be
  • If $Var(T_2) < Var(T_1)$, then $T_2$ is
  • If $f(x_1,x_2,\cdots,x_n;\theta)=g(\hat{\theta};\theta)h(x_1,x_2,\cdots,x_n)$, then $\hat{\theta}$ is
  • Which of the following assumptions are required to show the consistency, unbiasedness, and efficiency of the OLS estimator?
    i. $E(\mu_t)=0$
    ii. $Var(\mu_t)=\sigma^2$
    iii. $Cov(\mu_t,\mu_{t-j})=0;t\neq t-j$
    iv. $\mu_t \sim N(0,\sigma^2)$
  • For a biased estimator $\hat{\theta}$ of $\theta$, which one is correct
  • A test is said to be the most powerful test of size $\alpha$, if
  • In statistical inference, the best asymptotically normal estimator is denoted by
  • If the conditional distribution of $X_1, X_2,\cdots,X_n$ given $S=s$, does not depend on $\theta$, for any value of $S=s$, the statistics $S=s(X_1,X_2,\cdots,X_n)$ is called
  • A set of jointly sufficient statistics is defined to be minimal sufficient if and only if
  • If $X_1,X_2,\cdots, X_n$ is the joint density of n random variables, say, $f(X_1, X_2,\cdots, X_n;\theta)$ which is considered to be a function of $\theta$. Then $L(\theta; X_1,X_2,\cdots, X_n)$ is called
  • For two estimators $T_1=t_1(X_1,X_2,\cdots,X_n)$ and $T_2=t_2(X_1,X_2,\cdots,X_n)$ then estimator $t_1$ is defined to be $R_{{t_1}(\theta)}\leq R_{{t_2}(\theta)}$ for all $\theta$ in $\Theta$
  • Let $X_1,X_2,\cdots,X_n$ be a random sample from the density $f(x;\theta)$, where $\theta$ may be vector. If the conditional distribution of $X_1,X_2,\cdots,X_n$ given $S=s$ does not depend on $\theta$ for any value of $s$ of $S$, then statistic is called.
  • $Var_\theta (T) \geq \frac{[\tau'(\theta)]^2}{nE[{\frac{\partial}{\partial \theta}log f((X;\theta)}^2]}$, where $T=t(X_1,X_2,\cdots, X_n)$ is an unbiased estimator of $\tau(\theta)$. The above inequality is called
  • Let $X_1,X_2,\cdots,X_n$ be a random sample from a density $f(x|\theta)$, where $\theta$ is a value of the random variable $\Theta$ with known density $g_\Theta(\theta)$. Then the estimator $\tau(\theta)$ with respect to the prior $g_\Theta(\theta)$ is defined as $E[\tau(\theta)|X_1,X_2,\cdots,X_n]$ is called
  • Let $L(\theta;X_1,X_2,\cdots,X_n)$ be the likelihood function for a sample $X_1,X_2,\cdots, X_n$ having joint density $f(x_1,x_2,\cdots,x_n;\theta)$ where ? belong to parameter space. Then a test defined as $\lambda=\lambda_n=\lambda(x_1,x_2,\cdots,x_n)=\frac{Sup_{\theta\varepsilon \Theta_0}L(\theta;x_1,x_2,\cdots,x_n)}{Sup_{\theta\varepsilon \Theta}L(\theta;x_1,x_2,\cdots,x_n)}$
  • Let $Z_1,Z_2,\cdots,Z_n$ be independently and identically distributed random variables, satisfying $E[|Z_t|]<\infty$. Let N be an integer-valued random variable whose value $n$ depends only on the values of the first n $Z_i$s. Suppose $E(N)<\infty$, then $E(Z_1+Z_2+\cdots+Z_n)=E( N)E(Z_i)$ is called
  • What is the maximum expected difference between a population parameter and a sample estimate?
  • Which of the following statements describes an interval estimate?
  • What are the main components of a confidence interval?

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