T test as a parametric statistic
By Tae Kyun Kim. Korean Journal of Anesthesiology, 2015
1,363 citations recorded by the source corpus.
In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ2) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ2/n). Under the null hypothesis µ = µ0, the distribution of statistics z=X¯-µ0σ/n should be standardized as a normal distribution. When the variance of the population is not known, replacement with the sample variance s2 is possible. In this case, the statistics X¯-µ0s/n follows a t distribution (n-1 degrees of freedom). An independent-group t test can be carried out for a comparison of means between two independent groups, with a paired t test for paired data. As the t test is a parametric test, samples should meet certain preconditions, such as normality, equal variances and independence.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/c34108eb9bddf4f8d11f13be25cd9bc5530ea22b
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