在概率论和统计学中，学生t-分布（Student's t-distribution），可简称为t分布。应用在估计呈正态分布的母群体之平均数。它是对两个样本均值差异进行显着性测试的学生t检定的基础。学生t检定改进了Z检定（Z-test），因为Z检定以母体标准差已知为前提。虽然在样本数量大（超过30个）时，可以应用Z检定来求得近似值，但Z检定用在小样本会产生很大的误差，因此必须改用学生t检定以求准确。

在母体标准差未知的情况下，不论样本数量大或小皆可应用学生t检定。在待比较的数据有三组以上时，因为误差无法压低，此时可以用变异数分析（ANOVA）代替学生t检定。

In probability and statistics, Student's t-distribution (or simply the t-distribution) is any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown. It was developed by William Sealy Gosset under the pseudonym Student. Whereas a normal distribution describes a full population, t-distributions describe samples drawn from a full population; accordingly, the t-distribution for each sample size is different, and the larger the sample, the more the distribution resembles a normal distribution.