# Statistics MCQs for Exams & Jobs Test Preparation

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 Statistical Methods MCQs Survival Analysis MCQS Regression Analysis MCQs Operations Research MCSQ Statistical Quality Control MCQs Design & Analysis of Experiments 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

C) Point Estimation

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

A) Statistical Inference

3. The expected value of loss function is called:
A) Risk function
B) Posterior density
C) Prior density
D) None of these

A) Risk function

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

B) θ ≠ θ0

5. If θ ̂ is unbiased estimator of θ then Var (θ ̂) ———- MSE (θ ̂).
A) =
B) >
C) <
D) None of these

A) =

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

D) Kolmogorov Simornov Test

7. Run test is used to test the ————- of observations.
A) Mean
B) Median
C) Randomness
D) None of these

C) Randomness

8. Wilcoxon Rank Sum test is a —————— test.
A) Parametric
B) Non Parametric
C) Both (A) & (B)
D) None of these

B) Non Parametric

9. Bartlett’s test is used to test the equality of several population:
A) Correlations
B) Means
C) Variances
D) None of these

C) Variances

10. Goldfield Quandt test is used to detect:
A) Heteroscedasticity
B) Multicollinearity
C) Autocorrelation
D) Homoscedasticity

A) Heteroscedasticity

11. When an observation is incomplete deliberately then it is called:
A) Censoring
B) Truncation
C) Both (A) & (B)
D) None of these

C) Both (A) & (B)

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

B) Distributed Lag Model

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

A) Censoring

14. Statistical ————— deals with the conclusions about parameters through sample data.
A) Hypothesis
B) Inference
C) Methods
D) None of these

B) Inference

15. MLE becomes asymptotically efficient if n → :
A) 10
B) 12
C) 15
D) ∞

D) ∞

16. The repetition of the basic experiment is called:
A) Randomization
B) Replication
C) Local Control
D) None of these

B) Replication

17. The experimental units should be ———– in CR design.
A) Homogeneous
B) Heterogeneous
C) Both (A) & (B)
D) None of these

A) Homogeneous

18. In Latin Square design ———– way variation is controlled.
A) One
B) Two
C) Three
D) Four

B) Two

19. Basic principles of the experimental designs are:
A) Randomization
B) Replication
C) Local Control
D) All of these

D) All of these

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

B) Partial confounding

21. Any characteristic of population is called
A) Parameter
B) Statistic
C) Estimator
D) Estimate

A) Parameter

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

C) Proportional

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

D) None of these

24. Var(y ̅st)opt ———— Var(y ̅ran).
A) =
B) ≠
C) >
D) ≤

D) ≤

25. Simple random sampling is suitable when population is:
A) Heterogeneous
B) Finite
C) Homogeneous
D) None of these

C) Homogeneous

26. The central composite design is composed of
A) Factorial points
B) Axial points
C) Center points
D) All of these

D) All of these

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

C) Rotatable

28. If there are two treatments in Latin square design then error degree freedom will be:
A) 2
B) 4
C) 1
D) 0

D) 0

29. In factorial experiment, Sign table method and Yates method give ————– results.
A) Same
B) Different
C) Both (A) & (B)
D) None of these

A) Same

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

B) Right

31. M. D of normal deviation is:
A) 0.7979 σ
B) 0.6745 σ
C) σ
D) None of these

A) 0.7979 σ

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)

D) P(A). P(B)

33. If Z is S.N.V then its mean is zero and variance is
A) σ2
B) σ
C) 1
D) 0

C) 1

34. If A & B are mutually exclusive events then A∩B = ————.
A) B
B) S
C) φ
D) A

C) φ

35. In rolling two fair dice, number of all possible elements are:
A) 36
B) 18
C) 12
D) 6

A) 36

36) Binomial probability distribution will be negatively skewed when
A) p > q
B) p < q
C) p = q
D) p ≠ q

A) p > q

37. In poison distribution mean = 4 then its S.D will be
A) 4
B) 8
C) 16
D) 2

D) 2

38. In normal distribution β1 = 0 and β2 = ———-.
A) 1
B) 2
C) 3
D) 0

C) 3

39. Probability of occurrence an event never be:
A) Positive
B) Negative
C) 1
D) 0

B) Negative

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

A) Gamma

41. ———– distribution is also called double exponential dist.
A) Gamma
B) Beta
C) Laplace
D) Uniform

C) Laplace

42. If f(x) = 2x, 0 < x < 1 then its F(x) will be
A) x
B) x2
C) 2×2
D) x3

B) x2

43. Mean does not exists of ————- probability distribution.
A) Gamma
B) Beta
C) Cauchy
D) Uniform

C) Cauchy

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

A) Exponential

45. If M.D = (β-α)/4 then it is ————— probability distribution.
A) Gamma
B) Beta type I
C) Beta Type II
D) Uniform

D) Uniform

46. Correlation coefficients is ————- of two regression coefficients.
A) A. M
B) G. M
C) H. M
D) All of these

B) G. M

47. Correlation coefficient lies between
A) -1 and +1
B) 0 and 1
C) -1 and 0
D) -0.5 and 0.5

A) -1 and +1

48. One of the classical assumptions to apply OLS is Cov (Ui, Uj) = ——–.
A) Positive
B) Negative
C) 0
D) None of these

C) 0

49. If there exist a linear relationship among regressors (x’s) there is:
A) Heteroscedasticity
B) Multicollinearity
C) Autocorrelation
D) None of these