Splunk Core Certified Advanced Power User Practice Test 2025 – The Comprehensive All-in-One Guide to Exam Success!

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How does the sample variance differ from the population variance?

Sample variance considers all field values

Population variance considers only a subset of values

Sample variance uses n-1 in its calculation

The sample variance is calculated using \( n - 1 \) in its formula, where \( n \) is the number of observations in the sample. This adjustment is known as Bessel's correction and is made to provide an unbiased estimate of the population variance from which the sample is drawn. The rationale behind using \( n - 1 \) instead of \( n \) is that when calculated from a sample, the variance tends to underestimate the true population variance. By using \( n - 1 \), the sample variance compensates for this bias, making it a more accurate representation of the variability in the overall population.

Population variance, on the other hand, uses \( n \) in its calculation because it includes all data points from the entire population without any need for correction. Understanding this distinction is crucial for correctly applying statistical methods in a variety of contexts, such as research, sampling techniques, and data analysis.

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Population variance uses n-2 in its calculation

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