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#has-images #reading-8-statistical-concepts-and-market-returns
Question
The formula for computing variance in a sample is:
s2 = [...]
s2 = [...]
Answer
Tags
#has-images #reading-8-statistical-concepts-and-market-returns
Question
The formula for computing variance in a sample is:
s2 = [...]
s2 = [...]
Answer
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Tags
#has-images #reading-8-statistical-concepts-and-market-returns
Question
The formula for computing variance in a sample is:
s2 = [...]
s2 = [...]
Answer
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Subject 6. Measures of Dispersion
n is where: μ = the mean N = the number of scores When the variance is computed in a sample, the statistic(m = the mean of the sample) can be used. However, s 2 is a biased estimate of σ 2 . By far <span>the most common formula for computing variance in a sample is: This gives an unbiased estimate of σ 2 . Since samples are usually used to estimate parameters, s 2 is the most commonly used measure of variance
Subject 6. Measures of Dispersion
n is where: μ = the mean N = the number of scores When the variance is computed in a sample, the statistic(m = the mean of the sample) can be used. However, s 2 is a biased estimate of σ 2 . By far <span>the most common formula for computing variance in a sample is: This gives an unbiased estimate of σ 2 . Since samples are usually used to estimate parameters, s 2 is the most commonly used measure of variance
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