Assumption of normality

Definition

The assumption of normality in a t-test states that the population being sampled should follow a normal distribution. This assumption allows for accurate inference about parameters such as means and variances based on sample data.

Related terms

Central Limit Theorem (CLT): This theorem states that, regardless of the shape of the population distribution, if we take a sufficiently large random sample from it and calculate the means of those samples, those sample means will be approximately normally distributed.

Skewness: This term refers to the asymmetry or lack of symmetry in a probability distribution. A normal distribution has zero skewness.

Kurtosis: This term measures the "tailedness" or peakedness/flatness of a probability distribution. A normal distribution has a kurtosis value of 3 (mesokurtic).