Small sample sizes refer to a limited number of observations or data points collected for analysis, which can lead to increased variability and uncertainty in statistical estimates. When working with small sample sizes, the sampling distribution of the mean may not be normally distributed, which can affect the reliability of conclusions drawn from the data. Understanding the implications of small sample sizes is crucial in statistics, especially when determining confidence intervals and hypothesis testing.
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