7.SP.1 - Population vs. Sample & Biased vs. Unbiased

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What is a population in statistics?

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A population is the entire group of individuals or items that we want to study or gather information about.

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What is a sample in statistics?

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A sample is a subset of the population that is selected for the purpose of conducting a study.

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What does it mean for a sample to be random?

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A random sample is one where every member of the population has an equal chance of being selected.

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What is a biased sample?

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A biased sample is one that does not accurately represent the population, often due to a flawed selection process.

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What is an unbiased sample?

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An unbiased sample accurately reflects the characteristics of the population from which it is drawn.

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Why is it important to have a random sample?

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A random sample helps ensure that the results of a study can be generalized to the entire population.

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What is the difference between a population and a sample?

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A population includes all members of a defined group, while a sample includes only a portion of that group.

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How can you create a random sample?

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You can create a random sample by using methods like drawing names from a hat or using random number generators.

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What is sampling bias?

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Sampling bias occurs when certain members of the population are more likely to be selected than others, leading to an unrepresentative sample.

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What is a stratified sample?

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A stratified sample is created by dividing the population into subgroups and then taking a random sample from each subgroup.