# Solved Sampling Techniques MCQs – Statistics Quiz

## Course Objectives

Sampling Techniques MCQs to explain the logic of sampling and different related concepts.To enable the student to decide what kind of sampling technique to be adopted for a given type of population. How population unknown values are estimated on the basis of information obtained from sample. How the efficiencies of different sampling designs differ.

## Topics of MCQs

Cluster Sampling MCQs : reasons for using the cluster sampling, examples of clusters of equal and unequal sizes, single stage cluster sampling for clusters of equal sizes, notations, mean per unit and mean per element, variance within clusters, variance between clusters, correlation, anova table for population and sample.

Relationship between cluster sampling and systematic random sampling, unbiasedness of sample mean and variance of the sample mean per element, in case of single-stage cluster sampling of equal-sized clusters. Variance of the cluster sample in terms of intra-cluster correlation.

Clusters of unequal sizes, unbiased estimate of population total and its variance, simple random sample of clusters: ratio-to-size estimation, sampling with probability proportional to size, selection with unequal probabilities with replacement.

Sampling with unequal probabilities without replacement, Horvitz-Thompson estimator, Brewer’s method. Subsampling with units of equal sizes, primary sampling units and secondary sampling units, two-stage cluster sampling

The general expression for the variance of an estimator in case of 2-stage sampling, mean of two-stage cluster sample and its variance, sample estimation of variance.

Three-stage sampling, examples of three-stage cluster sampling, general expression for the variance of an estimator in case of three-stage sampling, mean of three stage cluster sample and its variance.

Subsampling with clusters of unequal sizes. Double sampling, double sampling for stratification. Sources of errors in surveys, effects of non-response, types of non response, errors of measurements. Bias.

### Sampling Techniques MCQs

Regression method of estimation is used to get.
A. small variance
B. large variance
C. unbiased variance
D. biased but consistent variance

A. small variance

A questionnaire consists of set of queries about a.
A. specific issue
B. sample
C. population
D. sample design

A. specific issue

Regression method of estimation was introduced by.
A. R A Fisher
B. Karl Pearson
C. Watson
D. Cochran

C. Watson

In regression method of estimation ß is.
A. independent variable
B. dependent variable
C. slope of the line
D. regression coefficient

C. slope of the line

Regression estimation can be made in.
A. one way
B. two way
C. three way
D. none of the above

B. two way

The bias is negligible in.
A. large samples
B. small samples
C. ratio
D. sample mean

A. large samples

Read Also >> Basic Statistical Inference MCQs

In regression method of estimation sample mean is an unbiased estimate of the population.
A. total
B. mean
C. ratio
D. variance

B. mean

In regression method of estimation sample variance is smaller than variance of.
A. ratio method of estimation
B. stratified random sample
C. simple random sample
D. all above

C. simple random sample

Regression method was introduced in.
A. 1925
B. 1937
C. 1940
D. 1938

B. 1937

Ratio method of estimation is not applicable when regression line is passing.
A. not through origin
B. through origin
C. through y-axis
D. through x-axis

A. not through origin

Sampling techniques was written by.
A. William G Cochran
B. Ronald A Fisher
C. Kish
D. Deming

A. William G Cochran

A. John Wiley and Sons
B. McGraw Hill
C. Chapman& Hall
D. Macmillan

A. John Wiley and Sons

We prefer regression method when line passes through the origin.
A. True
B. False

B. False

The ratio estimate of population total can be done only separately.
A. True
B. False

B. False

Bias and relative bias are two different estimates.
A. True
B. False

A. True

In ratio method of estimation sample mean is a consistent estimate of population mean.
A. True
B. False

A. True

A sample of cluster is selected at random.
A. True
B. False

B. False

Regression model with stochastic term is called random model.
A. True
B. False

A. True

Systematic sampling demands the selection of single sampling unit.
A. True
B. False

A. True

The estimate of ratio in ratio method of estimation is consistent estimate of population ratio.
A. True
B. False

A. True

Regression model with stochastic term is called exact model.
A. True
B. False

B. False

Systematic sampling is imprecise when the unit in sample is homogeneous.
A. True
B. False

A. True

If sample size is large sample mean to approaches to population mean.
A. True
B. False

A. True

In regression method of estimation the auxiliary variate (Xi) is correlated with.
A. Xi
B. Yi
C. Ri
D. Xi & Yi

B. Yi

b is.
A. estimate of change
B. change in y due to x
C. constant
D. variable

B. change in y due to x

In regression method of estimation b and B are.
A. same
B. constant
C. variable
D. sample and population regression coefficient respectively

D. sample and population regression coefficient respectively

If b – B = 0. It means that.
A. MSE is zero
B. sampling error not ignored
C. sampling error ignored
D. variance zero

C. sampling error ignored

To compare ratio, regression and simple random sampling, the sample size should be.
A. small
B. large
C. two
D. 8

B. large

If ? > 0 variance of regression is superior than.
A. simple random sample
B. ratio estimate
C. stratified random sampling
D. cluster sampling

A. simple random sample

Simple random sampling and systematic sampling are.
A. probability sampling
B. non probability sampling
C. quota sampling
D. time sampling

A. probability sampling

In systematic sampling we divide.
A. population into nth parts
B. population into N equal of kit unit each
C. population
D. sample

B. population into N equal of kit unit each

In systematic sampling the first selection of unit determines the.
A. first sample
B. last sample
C. whole sample
D. none of the above

C. whole sample

Regression method of estimation was introduced to increase.
A. variance
B. error
C. precision
D. accuracy

C. precision

Systematic sample is as precise as stratified random sample when one unit is drawn from.
A. population
B. each unit
C. each group
D. each stratum

D. each stratum

Systematic sampling demands the selection of single complex.
A. sampling frame
B. frame
C. sampling design
D. sampling unit

C. sampling design

The cluster may be.
A. equal
B. unequal
C. equal or unequal
D. constant

C. equal or unequal

Clusters are known as.
A. PSU
B. SSU
C. BSU
D. MSU

A. PSU

The performance of systematic sampling depends on.
A. sample size
B. population
C. properties of population
D. characteristics of sample

C. properties of population

In cluster sampling units are found in the form of.
A. aggregate
B. groups
C. cluster
D. stratum

B. groups

Cluster sampling is a type of.
A. purposive sampling
B. quota sampling
C. probability sampling
D. non probability sampling

C. probability sampling

Clusters are
A. similar to stratum
B. homogeneous
C. dissimilar to stratum
D. systematic sample

C. dissimilar to stratum

Regression estimation can be made in.
A. one way
B. two way
A. three way
B. none of the above

B. two way

The bias is negligible in.
A. large samples
B. small samples
C. ratio
D. sample mean

B. small samples

In regression method of estimation sample total is an unbiased estimate of the population.
A. total
B. mean
C. ratio
D. variance

A. total

In regression method of estimation sample ratio is an unbiased estimate of the population.
A. total
B. mean
C. ratio
D. variance

C. ratio

Cluster sampling is a non-probability sampling technique.
A. True
B. False

B. False

Regression model without stochastic term is called exact model.
C. True
D. False

C. True

When regression line passes through the origin, sample ratio is an unbiased estimate of population ratio.
A. True
B. False

A. True

In systematic sampling first element is selected randomly.
A. True
B. False