The issue of the amount of difference between the mean of the population the sample is from and the mean of the null hypothesis population is the issue of one- or two-tailed tests critical value effect size Type I and Type II errors
Added by Tammy B.
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Effect size measures the magnitude of the difference between two groups or conditions, in this case, the difference between the sample mean and the null hypothesis population mean. Show more…
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The null hypothesis for a one sample t-test says that the mean in the population for the sample being tested is equal to some known mean. In other words, the null hypothesis claims that… even if the mean in the sample is different from the known mean, this is likely just due to random chance the population mean will always be greater than the sample mean the sample could not have come from a population with the known mean the sample mean is too small
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The null and alternate hypotheses are: H0: μ1 = μ2 H1: μ1 ≠μ2 A random sample of 10 observations from one population revealed a sample mean of 26 and a sample standard deviation of 6.0. A random sample of 8 observations from another population revealed a sample mean of 31 and a sample standard deviation of 7.0. The population standard deviations are unknown but assumed to be equal. At the 0.10 significance level, is there a difference between the population means?
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