sampling - random/biased/representative

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What is sampling?

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Sampling is the process of selecting a subset of individuals from a larger population to estimate characteristics of the whole population.

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What is a random sample?

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A random sample is a sample that is selected from a population in such a way that every individual has an equal chance of being chosen.

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What is a biased sample?

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A biased sample is a sample that does not accurately represent the population from which it is drawn, often due to systematic favoritism in the selection process.

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What is a representative sample?

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A representative sample is a subset of a population that accurately reflects the members of the entire population.

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Why is it important to have a representative sample?

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A representative sample ensures that the results of a survey or study can be generalized to the larger population.

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What can cause a sample to be biased?

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A sample can be biased due to factors like non-random selection, small sample size, or focusing on a specific group.

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What is the difference between random sampling and convenience sampling?

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Random sampling gives every individual an equal chance of being selected, while convenience sampling selects individuals who are easiest to reach.

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How can surveying the first few people in line lead to bias?

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Surveying the first few people may lead to bias because those individuals may not represent the entire population, as they might share similar characteristics.

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What is stratified sampling?

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Stratified sampling is a method where the population is divided into subgroups (strata) and random samples are taken from each stratum.

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What is the impact of sample size on the reliability of results?

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Larger sample sizes generally lead to more reliable results, as they reduce the margin of error and better represent the population.