• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.177-182
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• 2008

There are times when we need more sample to achieve a more accurate estimator. Since these two sets of sample have the information about the same population, it is necessary to treat both as a single combined data. In this paper we present the unpooled sample variance for the combined data when we just know a sample mean and variance for the each data set without the raw data. It is shown that the pooled variance $s^2_p$ is always greater than the exact variance $s^2_t$ when ${\bar{x}}_n\;=\;{\bar{y}}_m$. And the difference of means for two data, ${\bar{x}}_n-{\bar{y}}_m}$, is larger, the difference of $s^2_p$ and $s^2_t$ is larger.