Stat Analysis Bias vs. Unbiased

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What is the definition of an unbiased sample?

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An unbiased sample is one that accurately represents the population from which it is drawn, ensuring that every individual 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 systematic errors in the selection process, leading to skewed results.

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Why is random selection important in sampling?

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Random selection is important because it helps to eliminate bias, ensuring that every member of the population has an equal chance of being included in the sample.

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What is the impact of bias on statistical analysis?

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Bias can lead to incorrect conclusions, as it skews the results and does not accurately reflect the true characteristics of the population.

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What is a convenience sample?

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A convenience sample is a type of non-probability sampling where the sample is taken from a group that is easily accessible, which can introduce bias.

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How can stratified sampling reduce bias?

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Stratified sampling reduces bias by dividing the population into subgroups (strata) and randomly sampling from each subgroup, ensuring representation across key characteristics.

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What is the difference between qualitative and quantitative data?

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Qualitative data is descriptive and categorical, while quantitative data is numerical and can be measured.

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What is sampling error?

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Sampling error is the difference between the sample statistic and the actual population parameter, which can occur due to random chance.

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What is the role of sample size in reducing bias?

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A larger sample size generally reduces sampling error and increases the reliability of the results, making it less likely for bias to affect the outcome.

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What is a systematic sample?

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A systematic sample is a method where you select every nth individual from a list or sequence, which can introduce bias if there is a pattern in the population.