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What is a sample in statistics?

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A sample is a subset of individuals or observations selected from a larger population, used to estimate characteristics of the whole population.

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What is the margin of error?

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The margin of error is a statistic that expresses the amount of random sampling error in a survey's results, indicating the range within which the true population parameter is expected to fall.

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How is the margin of error calculated?

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The margin of error is typically calculated using the formula: ME = Z * (σ/√n), where Z is the Z-score corresponding to the desired confidence level, σ is the standard deviation, and n is the sample size.

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What does a 95% confidence level mean?

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A 95% confidence level means that if we were to take 100 different samples and compute a confidence interval for each sample, approximately 95 of the intervals would contain the true population parameter.

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What is bias in sampling?

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Bias in sampling refers to systematic errors that lead to an incorrect representation of the population, often resulting from non-random selection methods.

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What is variability in statistics?

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Variability refers to how spread out or dispersed the values in a data set are, indicating the degree of difference among the data points.

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How can we reduce variability in a sample?

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We can reduce variability by increasing the sample size, which helps to better represent the population and minimize the effects of outliers.

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What is random sampling?

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Random sampling is a technique where each member of the population has an equal chance of being selected, helping to ensure that the sample is representative.

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What is a confidence interval?

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A confidence interval is a range of values, derived from a sample, that is likely to contain the true population parameter with a specified level of confidence.

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What does high bias and low variability indicate?

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High bias and low variability indicate that the sample consistently overestimates or underestimates the true population parameter, but the estimates are close to each other.