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Testing a Sample Hypothesis
Testing a sample hypothesis

The theory behind testing the significances of the difference between a sample value and some other (sample or population) value involves determining whether the probability that the given difference might have occurred as a result of sampling variation is above or below a certain critical value. If the probability is below this critical preselected level, the difference is adjusted to be significant, i.e. a real difference exists, and it is not likely that the two values being tested are part of the same group or population. If the probability is above this critical level, this is taken to indicate that the sample is not from the actual population.

Key Features

The 0.05 significance level (equivalent to the 0.95 confidence coefficient) is ...

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