Two-Sample Statistical Tests, Normal Distribution

The two-sample comparative test can be considered the “workhorse” of microbial biostatistics. Here, one is evaluating two different sample groups such as treatments, methods, procedures, or product formulations, for example, to determine if the means of data differ, or if the mean for one is smaller or larger than that for the other. No matter what the test hypothesis, two sample sets are compared.

Key Point

There are three basic categories of test designs for the two-sample tests:
  1. 1.

    Two-Sample Independent t-Test. This test assumes the variances of the data from the two sample groups are independent and, therefore, one does not confirm that the two samples have the same variances, s2. Hence, they are considered different, \(\sigma _1^2 \ne \sigma _2^2 \)


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Copyright information

© Springer Science + Business Media, LLC 2008

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