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| Probability Distributions MCQs |
| Sampling Techniques MCQs |
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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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