T-test
A statistical test that compares means, either between two groups or against a reference value, to judge whether the difference is likely due to chance.
A t-test evaluates whether a difference in means is larger than sampling variation would explain. The independent-samples t-test compares two separate groups; the paired-samples t-test compares the same participants at two time points or under two conditions; the one-sample t-test compares a sample mean to a known value. Each produces a t statistic, degrees of freedom, and a p-value.
The test assumes approximately normally distributed data, or a reasonably large sample, and the independent version assumes similar variances across groups, with adjustments available when variances differ. For small non-normal samples, the Mann-Whitney U test is a common alternative.
In a thesis, t-tests suit clean two-group comparisons such as pre-post designs or treatment versus comparison groups. Report the means and standard deviations, the test statistic with its degrees of freedom, the p-value, and an effect size so the comparison is fully interpretable.
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