Sampling Theory In Statistics: Quiz! Test

42 Questions | By Sweetsalman123 | Updated: Mar 21, 2022 | Attempts: 947

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Sampling Theory In Statistics: Quiz! Test - Quiz

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1.

Sampling can be described as a statistical procedure:
- A.
  
  To infer about the unknown universe from a knowledge of any sample
- B.
  
  To infer about the known universe from a knowledge of a sample drawn from it
- C.
  
  To infer about the unknown universe from a knowledge of a random sample drawn from it
- D.
  
  Both (a) and (b)
2.

The Law of Statistical Regularity says that:
- A.
  
  Sample drawn from the population under discussion possesses the characteristics of the population
- B.
  
  A large sample drawn at random from the population would posses the characteristics of the population
- C.
  
  A large sample drawn at random from the population would possess the characteristics of the population on an average
- D.
  
  An optimum level of efficiency can be attained at a minimum cost
3.

A sample survey is prone to:
- A.
  
  Sampling errors
- B.
  
  Non-sampling errors
- C.
  
  Either (a) or (b)
- D.
  
  Both (a) and (b)
4.

The population of roses in Salt Lake City is an example of:
- A.
  
  A finite population
- B.
  
  An infinite population
- C.
  
  A hypothetical population
- D.
  
  An imaginary population
5.

Statistical decision about an unknown universe is taken on the basis of:
- A.
  
  Sample observations
- B.
  
  A sampling frame
- C.
  
  Sample survey
- D.
  
  Complete enumeration
6.

Random sampling implies:
- A.
  
  Haphazard sampling
- B.
  
  Probability sampling
- C.
  
  Systematic sampling
- D.
  
  Sampling with the same probability for each unit
7.

A parameter is a characteristic of:
- A.
  
  Population
- B.
  
  Sample
- C.
  
  Both (a) and (b)
- D.
  
  (a) or (b)
8.

A statistic is:
- A.
  
  A function of sample observations
- B.
  
  A function of population units
- C.
  
  A characteristic of a population
- D.
  
  A part of a population
9.

Sampling Fluctuations may be described as:
- A.
  
  The variation in the values of a statistic
- B.
  
  The variation in the values of a sample
- C.
  
  The differences in the values of a parameter
- D.
  
  The variation in the values of observations
10.

The sampling distribution is:
- A.
  
  The distribution of sample observations
- B.
  
  The distribution of random samples
- C.
  
  The distribution of a parameter
- D.
  
  The probability distribution of a statistic
11.

Standard error can be described as:
- A.
  
  The error committed in sampling
- B.
  
  The error committed in sample survey
- C.
  
  The error committed in estimating a parameter
- D.
  
  Standard deviation of a statistic
12.

A measure of precision obtained by sampling is given by:
- A.
  
  Standard error
- B.
  
  Sampling fluctuation
- C.
  
  Sampling distribution
- D.
  
  Expectation
13.

As the sample size increases, standard error:
- A.
  
  Increases
- B.
  
  Decreases
- C.
  
  Remains constant
- D.
  
  Decrease proportionately
14.

If from a population with 25 members, a random sample without replacement of 2 members is taken, the number of all such samples is:
- A.
  
  300
- B.
  
  625
- C.
  
  50
- D.
  
  600
15.

A population comprises 5 members. The number of all possible samples of size 2 that can be drawn from it with replacement is:
- A.
  
  100
- B.
  
  15
- C.
  
  125
- D.
  
  25
16.

Simple random sampling is very effective if:
- A.
  
  The population is not very large
- B.
  
  The population is not much heterogeneous
- C.
  
  The population is partitioned into several sections
- D.
  
  Both (a) and (b)
17.

Simple random sampling is:
- A.
  
  A probabilistic sampling
- B.
  
  A non-probabilistic sampling
- C.
  
  A mixed sampling
- D.
  
  Both (b) and (c)
18.

According to Neyman's allocation, in stratified sampling:
- A.
  
  Sample size is proportional to the population size
- B.
  
  Sample size is proportional to the sample SD
- C.
  
  Sample size is proportional to the sample variance
- D.
  
  Population size is proportional to the sample variance
19.

Which sampling provides separate estimates for population means for different segments and also an overall estimate?
- A.
  
  Multistage sampling
- B.
  
  Stratified sampling
- C.
  
  Simple random sampling
- D.
  
  Systematic sampling
20.

Which sampling adds flexibility to the sampling process?
- A.
  
  Simple random sampling
- B.
  
  Multistage sampling
- C.
  
  Stratified sampling
- D.
  
  Systematic sampling
21.

Which sampling is affected most if the sampling frame contains an undetected periodicity?
- A.
  
  Simple random sampling
- B.
  
  Stratified sampling
- C.
  
  Multistage sampling
- D.
  
  Systematic sampling
22.

Which sampling is subjected to the discretion of the sampler?
- A.
  
  Systematic sampling
- B.
  
  Simple random sampling
- C.
  
  Purposive sampling
- D.
  
  Quota sampling
23.

The criteria for an ideal estimator are:
- A.
  
  Unbiasedness, consistency, efficiency and sufficiency
- B.
  
  Unbiasedness, expectation, sampling and estimation
- C.
  
  Estimation, consistency, sufficiency and efficiency
- D.
  
  Estimation, expectation, unbiasedness and sufficiency
24.

The sample standard deviation is:
- A.
  
  A biased estimator
- B.
  
  An unbiased estimator
- C.
  
  A biased estimator for population SD
- D.
  
  A biased estimator for population variance
25.

The sample mean is:
- A.
  
  An MVUE for population mean
- B.
  
  A consistent and efficient estimator for population mean
- C.
  
  A sufficient estimator for population mean
- D.
  
  All of these