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.
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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.