Distribution Tables — Z, T, Chi-Square, F

Look up critical values from z, t, chi-square and F distributions for hypothesis testing.

About this calculator

A distribution table reference provides critical values and tail probabilities for the most-used probability distributions: standard normal (z), Student's t, chi-square (χ²), and F distribution. These tables are essential for hypothesis testing, confidence interval construction, and any quantitative statistical inference.

The standard normal distribution (mean 0, sd 1) underpins everything in classical statistics. Z = (X − μ)/σ converts any normal distribution to standard normal so a single table covers all cases. The t-distribution accommodates small samples; chi-square handles variance and goodness-of-fit; F handles ratios of variances.

Worked example

Inputs: Common critical values for two-tailed α = 0.05

  1. Standard normal: ±1.960
  2. t-distribution, df=10: ±2.228
  3. t-distribution, df=30: ±2.042
  4. t-distribution, df→∞: ±1.960 (approaches z)
  5. Chi-square (df=10, upper 0.05): 18.31
  6. F (df1=5, df2=10, upper 0.05): 3.33

Frequently asked questions

When do I use z-distribution vs t-distribution?

Use z (standard normal) when the population standard deviation σ is known, or when the sample size is large (n > 30) and you are using the sample standard deviation s as a stand-in. Use t when σ is unknown and the sample is small (n < 30). The t-distribution has heavier tails to account for the extra uncertainty from estimating σ; as n grows, t converges to z.

What is degrees of freedom?

Degrees of freedom (df) measure the number of independent pieces of information in your data set after using some to estimate parameters. For a sample variance computed from n data points, df = n − 1 because one degree was used to estimate the mean. For chi-square goodness-of-fit on k categories with one parameter estimated, df = k − 2. Always check the specific df rule for the test you are using.

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