The T-DISTRIBUTION is a probability distribution that has a mean of 0 and is symmetrical and bell-shaped, similar to the normal distribution, but with heavier tails. The t-distribution provides a more accurate and conservative estimates of population parameters when dealing with small samples (n<30) or when population standard deviations are unknown (which is usually the case in social science research).
The shape of the t-distribution — how tall/short the center of the distribution is and how thin/thick the tails of the distribution are (i.e., the dispersion of the distribution) — is determined by the DEGREES OF FREEDOM (df). The degrees of freedom for a single sample is equal to the sample size, minus one; as a formula: df=n-1. As degrees of freedom increase, the t-distribution approaches the normal distribution.
To interpret a t-distribution, you will need to reference a T-DISTRIBUTION TABLE (i.e., a T-TABLE). Using a t-table is similar to using a z-table:
- Rows correspond to different degrees of freedom
- Columns correspond to different confidence levels (90%, 95%, 99%) or SIGNIFICANCE LEVELS (α), which are equal to 1 minus the confidence level (α = 0.10, 0.05, 0.01)
- Table cells report the CRITICAL VALUES of the t-distribution, given the degrees of freedom and the confidence level/significance level; critical values are helpful in hypothesis testing and determining confidence intervals
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