true
A small sample size and a large sample variance.
The standard deviation is defined as the square root of the variance, so the variance is the same as the squared standard deviation.
Square the standard deviation to obtain the variance. The variance is 62 or 36.
Standard deviation is the square root of the variance; so if the variance is 64, the std dev is 8.
The square of the standard deviation is called the variance. That is because the standard deviation is defined as the square root of the variance.
no
Standard deviation is the square root of the variance.
They would both increase.
A small sample size and a large sample variance.
The sample variance (s²) is calculated using the formula ( s² = \frac{SS}{n - 1} ), where SS is the sum of squares and n is the sample size. For a sample size of n = 9 and SS = 72, the sample variance is ( s² = \frac{72}{9 - 1} = \frac{72}{8} = 9 ). The estimated standard error (SE) is the square root of the sample variance divided by the sample size, calculated as ( SE = \sqrt{\frac{s²}{n}} = \sqrt{\frac{9}{9}} = 1 ). Thus, the sample variance is 9 and the estimated standard error is 1.
Sample variance directly influences the estimated standard error, as the standard error is calculated using the sample variance divided by the square root of the sample size. A higher sample variance results in a larger standard error, indicating greater uncertainty in the estimate of the population parameter. For effect size measures like ( r^2 ) and Cohen's D, increased sample variance can affect their interpretation; larger variance may lead to smaller effect sizes, suggesting that the observed differences are less pronounced relative to the variability in the data. Thus, understanding sample variance is crucial for accurate estimation and interpretation of effect sizes.
http://www.futureaccountant.com/standard-costing-variance-analysis/ http://www.futureaccountant.com/standard-costing-variance-analysis/
standard costing and variance analysis
No. The standard deviation is the square root of the variance.
Square the standard deviation and you will have the variance.
Yes. If the variance is less than 1, the standard deviation will be greater that the variance. For example, if the variance is 0.5, the standard deviation is sqrt(0.5) or 0.707.
Standard deviation = square root of variance.