Non-statistical sampling can be categorized into which two types?

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Multiple Choice

Non-statistical sampling can be categorized into which two types?

Explanation:
Non-statistical sampling is choosing samples without using random processes or known inclusion probabilities. In practice, this falls into two main forms: biased sampling and judgmental sampling. Biased sampling happens when the way you select samples favors certain outcomes or groups, whether on purpose or due to design flaws. This makes the sample unrepresentative of the whole population and can skew results, limiting how well findings reflect real conditions. Judgmental sampling relies on the investigator’s expertise to pick samples they believe are representative or informative. It can be efficient and useful for exploratory work, but it depends on subjective judgment and doesn’t provide objective measures of representativeness or random chance of inclusion. The other listed methods rely on probability or randomization to ensure representativeness, so they’re considered statistical rather than non-statistical.

Non-statistical sampling is choosing samples without using random processes or known inclusion probabilities. In practice, this falls into two main forms: biased sampling and judgmental sampling.

Biased sampling happens when the way you select samples favors certain outcomes or groups, whether on purpose or due to design flaws. This makes the sample unrepresentative of the whole population and can skew results, limiting how well findings reflect real conditions.

Judgmental sampling relies on the investigator’s expertise to pick samples they believe are representative or informative. It can be efficient and useful for exploratory work, but it depends on subjective judgment and doesn’t provide objective measures of representativeness or random chance of inclusion.

The other listed methods rely on probability or randomization to ensure representativeness, so they’re considered statistical rather than non-statistical.

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