Statistics MCQs for Exams & Jobs Test Preparation

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We are offering you Solved Statistics MCQs for Online Exams like BS Statistic , MSc Statistic ,BBA, MBA, University Statistic Entrance exams and different Statistics related Jobs Test  like FPSC , PPSC ,SPSC , KPSC ,NTS .

Types of Statistics MCQs
Basic Statistical Inference MCQs
Probability Distributions MCQs
Sampling Techniques MCQs
Statistical Packages MCQs for Social Science
Statistical Methods MCQs
Survival Analysis MCQS
Regression Analysis MCQs
Operations Research MCSQ
Statistical Quality Control MCQs

Solved Statistics MCQs

1. A process to get a single value as an estimate of parameter on the basis of sample observation is called:
A) Interval Estimation
B) Estimator
C) Point Estimation
D) All of these
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2. ———— is an art of drawing conclusions about the unknown parameter on the basis of sample observation.
A) Statistical Inference
B) Sample
C) Sampling
D) None of these
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3. The expected value of loss function is called:
A) Risk function
B) Posterior density
C) Prior density
D) None of these
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4. We use Likelihood Ratio test to test H0: θ = θ0 Vs H1:
A) θ > θ0
B) θ ≠ θ0
C) θ < θ0
D) None of these
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5. If θ ̂ is unbiased estimator of θ then Var (θ ̂) ———- MSE (θ ̂).
A) =
B) >
C) <
D) None of these
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6. Non parametric test used to test the goodness of fit is:
A) Sign Test
B) Run Test
C) Kruskall Wallis Test
D) Kolmogorov Simornov Test
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7. Run test is used to test the ————- of observations.
A) Mean
B) Median
C) Randomness
D) None of these
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8. Wilcoxon Rank Sum test is a —————— test.
A) Parametric
B) Non Parametric
C) Both (A) & (B)
D) None of these
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9. Bartlett’s test is used to test the equality of several population:
A) Correlations
B) Means
C) Variances
D) None of these
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10. Goldfield Quandt test is used to detect:
A) Heteroscedasticity
B) Multicollinearity
C) Autocorrelation
D) Homoscedasticity
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11. When an observation is incomplete deliberately then it is called:
A) Censoring
B) Truncation
C) Both (A) & (B)
D) None of these
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12. A model in which lag values of regressors are also used as regressor, is called:
A) Autoregressive Model
B) Distributed Lag Model
C) Simple linear Regression Model
D) None of these
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13. When an observation is incomplete due to some random cause then it is called
A) Censoring
B) Truncation
C) Both (A) & (B)
D) None of these
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14. Statistical ————— deals with the conclusions about parameters through sample data.
A) Hypothesis
B) Inference
C) Methods
D) None of these
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15. MLE becomes asymptotically efficient if n → :
A) 10
B) 12
C) 15
D) ∞
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16. The repetition of the basic experiment is called:
A) Randomization
B) Replication
C) Local Control
D) None of these
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17. The experimental units should be ———– in CR design.
A) Homogeneous
B) Heterogeneous
C) Both (A) & (B)
D) None of these
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18. In Latin Square design ———– way variation is controlled.
A) One
B) Two
C) Three
D) Four
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19. Basic principles of the experimental designs are:
A) Randomization
B) Replication
C) Local Control
D) All of these
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20. If the different treatment combinations are confounded in different replications of a factorial experiment then it is called:
A) Complete confounding
B) Partial confounding
C) Both (A) & (B)
D) None of these
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21. Any characteristic of population is called
A) Parameter
B) Statistic
C) Estimator
D) Estimate
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22. Neyman allocation becomes exactly ————- allocation when the standard deviations of all strata are equal.
A) Equal
B) Optimum
C) Proportional
D) None of these
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23. Ignoring f. p. c. Var(y ̅st)Ney = ————-.
A) (∑▒whS2h)/n
B) (∑▒whSh)/n
C) (∑▒w_h^2 S_h^2)/n
D) None of these
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24. Var(y ̅st)opt ———— Var(y ̅ran).
A) =
B) ≠
C) >
D) ≤
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25. Simple random sampling is suitable when population is:
A) Heterogeneous
B) Finite
C) Homogeneous
D) None of these
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26. The central composite design is composed of
A) Factorial points
B) Axial points
C) Center points
D) All of these
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27. If the is equal at points equidistant from the center, design is called
A) First order
B) Orthogonal
C) Rotatable
D) None of these
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28. If there are two treatments in Latin square design then error degree freedom will be:
A) 2
B) 4
C) 1
D) 0
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29. In factorial experiment, Sign table method and Yates method give ————– results.
A) Same
B) Different
C) Both (A) & (B)
D) None of these
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30. ——– censoring occurs when a subject leaves the study before an event occurs.
A) Left
B) Right
C) Both (A) & (B)
D) None of these
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31. M. D of normal deviation is:
A) 0.7979 σ
B) 0.6745 σ
C) σ
D) None of these
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32. When A and B are independent then P(A∩B) = —————.
A) P(B)
B) P(A)
C) P(A/B)
D) P(A). P(B)
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33. If Z is S.N.V then its mean is zero and variance is
A) σ2
B) σ
C) 1
D) 0
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34. If A & B are mutually exclusive events then A∩B = ————.
A) B
B) S
C) φ
D) A
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35. In rolling two fair dice, number of all possible elements are:
A) 36
B) 18
C) 12
D) 6
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36) Binomial probability distribution will be negatively skewed when
A) p > q
B) p < q
C) p = q
D) p ≠ q
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37. In poison distribution mean = 4 then its S.D will be
A) 4
B) 8
C) 16
D) 2
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38. In normal distribution β1 = 0 and β2 = ———-.
A) 1
B) 2
C) 3
D) 0
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39. Probability of occurrence an event never be:
A) Positive
B) Negative
C) 1
D) 0
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40. M_0(t) = 〖(1-βt)〗^(-α) is moment generating function of ———— probability dist.
A) Gamma
B) Beta type I
C) Beta Type II
D) Uniform
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41. ———– distribution is also called double exponential dist.
A) Gamma
B) Beta
C) Laplace
D) Uniform
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42. If f(x) = 2x, 0 < x < 1 then its F(x) will be
A) x
B) x2
C) 2×2
D) x3
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43. Mean does not exists of ————- probability distribution.
A) Gamma
B) Beta
C) Cauchy
D) Uniform
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44. f(x) = 1/θ e^(〖-x/〗_θ ), x≥0 is p.d.f of ————— probability distribution.
A) Exponential
B) Gamma
C) Uniform
D) Beta
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45. If M.D = (β-α)/4 then it is ————— probability distribution.
A) Gamma
B) Beta type I
C) Beta Type II
D) Uniform
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46. Correlation coefficients is ————- of two regression coefficients.
A) A. M
B) G. M
C) H. M
D) All of these
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47. Correlation coefficient lies between
A) -1 and +1
B) 0 and 1
C) -1 and 0
D) -0.5 and 0.5
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48. One of the classical assumptions to apply OLS is Cov (Ui, Uj) = ——–.
A) Positive
B) Negative
C) 0
D) None of these
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49. If there exist a linear relationship among regressors (x’s) there is:
A) Heteroscedasticity
B) Multicollinearity
C) Autocorrelation
D) None of these
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50. If Ui is error term in simple linear regression model and Cov (Ui, Uj) ≠ 0, there is:
A) Heteroscedasticity
B) Multicollinearity
C) Autocorrelation
D) None of these
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