Which statement(s) apply to stratified random sampling? Check all that apply. A) It can provide better estimates than a simple random sample.
B) The researcher needs some knowledge of the population in terms of characteristics relevant to the study.
C) A challenge is that it is necessary to have strata of the same size.
D) Creating strata of similar individuals to sample from reduces variability.
E) It can be difficult to obtain with a very large population.

The statements that apply to stratified random sampling are;

A) It can provide better estimates than a simple random sample.

B) The researcher needs some knowledge of the population in terms of characteristics relevant to the study.

D) Creating strata of similar individuals to sample from reduces variability.

E) It can be difficult to obtain with a very large population.

Stratified random sampling is a method of sampling from a population that involves dividing the entire population into homogeneous groups that called strata.

The way it is done is that a random sample from each stratum is usually taken in a number that proportional to the size of the stratum if we compare it to the population size.

From the definitions above, the options that apply are, A, B, D and E.

Read more about stratified random sampling at; link

The correct options are;

A) It can provide better estimates than s simple random sample

B) The researcher needs some knowledge of the population in terms of characteristics relevant to the study

E) Creating strata of similar individuals reduces variability

Step-by-step explanation:

In order to reduce the variance in the population being studied the stratified sampling technique is used which consists of separating the given sample from the population into different strata based on known characteristics and finding out the result of the experiment in each strata. Each strata posses a common or shared attribute such as educational level or total level of income.

your answer   is c

step-by-step explanation:

step-by-step explanation: