![]() ![]() The p-value is the probability of obtaining sample results as extreme or more extreme than the sample results obtained, under the assumption that the null hypothesis is true ![]() The main principle of hypothesis testing is that the null hypothesis is rejected if the test statistic obtained is sufficiently unlikely under the assumption that the null hypothesis is true ![]() The main properties of a one sample t-test for one population mean are:įor a t-test for one mean, the sampling distribution used for the t-test statistic (which is the distribution of the test statistic under the assumption that the null hypothesis is true) corresponds to the t-distribution, with n-1 degrees of freedom (instead of being the standard normal distribution, as in the case of a z-test for one mean)ĭepending on our knowledge about the "no effect" situation, the t-test can be two-tailed, left-tailed or right-tailed The null hypothesis is a statement about the population mean, under the assumption of no effect, and the alternative hypothesis is the complementary hypothesis to the null hypothesis. The test has two complementary hypotheses, the null and the alternative hypothesis. How to Conduct a T-test for One Population Mean? This t-test, unlike the z-test, does not need to know the population standard deviation \(\sigma\). So you can better interpret the results obtained by this solver: A t-test for one mean is a hypothesis test that attempts to make a claim about the population mean (\(\sigma\)). How to use this t-test calculator for One Sample ![]()
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