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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.

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