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Pooled variance is a method for estimating variance given several different samples taken in different circumstances where the mean may vary between samples but the true variance (equivalently, precision) is assumed to remain the same.
A combined variance is a method for estimating variance from several samples, given the size, mean and standard deviation of each. Mathematically, a combined variance is equal to the calculated variance of the set of the data from all samples.
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How do you use variance analysis?
When data is homogeneous over k independent samples of size n_i for i=1,2,...,k, the pooled variance is given by s_p^2=((n_1-1) s_1^2+(n_2-1) s_2^2+⋯(n_k-1) s_k^2)/(n_1+n_2+⋯+n_k-k)
What does pooled data mean?
it means to rebulid
Which of the following best describes the condition necessary to justify using a pooled estimator of the population variance?
1- Assuming this represents a random sample from the population, the sample mean is an unbiased estimator of the population mean. 2-Because they are robust, t procedures are justified in this case. 3- We would use z procedures here, since we are interested in the population mean.
Using a pooled sample estimator for sigma squared assumes the two populations have what?
equal variances
What does pooled data set means?
is a data set with same variables but observed from different group of respondents
