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Random Sampling increases the reliability and validity of your research findings.

To begin with,

Reliability:

By randomly picking research participants, the likelihood that they are from different backgrounds/ have different experiences etc. is higher and hence, they are said to be more representative of the population of interest.

EG: RQ: Do females have higher IQ?

A case of random sampling will pick females who are housewives/ CEOs/ Indian/ 18yrs old/ Divorced etc. the list goes on.

While a case of non-random sampling (such as picking participants at a bus stop) may only result in a sample of females who are 20 - 35 years old, working professionals.

Validity: As reliability and validity are related, for the research findings to be reliable and generalizable to the population of interest, it first has to be a valid sample.

Hence, from the above example,

EG1 provides a valid sample, while EG2 is invalid.

Q: What kind of validity does the strategy of random sampling increase?

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yes

There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.

No.

Random sampling is picking a subject at random. Systematic sampling is using a pattern to pick subjects, I.e. picking every third person.

Quota sampling.

Related questions

THE RANDOM METHOD (: :P THE RANDOM METHOD (: :P THE RANDOM METHOD (: :P

You are correct; convenience sampling is not random sampling.

It can be but it is not simple random sampling.

a

yes

Simple!

Random Sampling

Simple Random Sample Stratified Random Sampling Cluster Sampling Systematic Sampling Convenience Sampling

There are many such methods: cluster sampling, stratified random sampling, simple random sampling.Their usefulness depends on the circumstances.

Compare the efficiency of simple random sampling with systematic random sampling for estimating the population mean and give your comments.

No.

That's a random question