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F Table: Critical Values of the F Distribution

Right-tail critical values of F for α = .10, .05, .025 and .01, with calculators for any degrees of freedom and for the p-value of your F statistic.

α = .10, .05, .025, .01df₁ 1 to ∞Printable (all four tables)

F table for α = 0.05

Critical values of the F distribution, α = 0.05
df₂ \ df₁1234567891012152024304060120∞
1161.45199.50215.71224.58230.16233.99236.77238.88240.54241.88243.91245.95248.01249.05250.10251.14252.20253.25254.31
218.5119.0019.1619.2519.3019.3319.3519.3719.3819.4019.4119.4319.4519.4519.4619.4719.4819.4919.50
310.139.559.289.129.018.948.898.858.818.798.748.708.668.648.628.598.578.558.53
47.716.946.596.396.266.166.096.046.005.965.915.865.805.775.755.725.695.665.63
56.615.795.415.195.054.954.884.824.774.744.684.624.564.534.504.464.434.404.36
65.995.144.764.534.394.284.214.154.104.064.003.943.873.843.813.773.743.703.67
75.594.744.354.123.973.873.793.733.683.643.573.513.443.413.383.343.303.273.23
85.324.464.073.843.693.583.503.443.393.353.283.223.153.123.083.043.012.972.93
95.124.263.863.633.483.373.293.233.183.143.073.012.942.902.862.832.792.752.71
104.964.103.713.483.333.223.143.073.022.982.912.852.772.742.702.662.622.582.54
114.843.983.593.363.203.093.012.952.902.852.792.722.652.612.572.532.492.452.40
124.753.893.493.263.113.002.912.852.802.752.692.622.542.512.472.432.382.342.30
134.673.813.413.183.032.922.832.772.712.672.602.532.462.422.382.342.302.252.21
144.603.743.343.112.962.852.762.702.652.602.532.462.392.352.312.272.222.182.13
154.543.683.293.062.902.792.712.642.592.542.482.402.332.292.252.202.162.112.07
164.493.633.243.012.852.742.662.592.542.492.422.352.282.242.192.152.112.062.01
174.453.593.202.962.812.702.612.552.492.452.382.312.232.192.152.102.062.011.96
184.413.553.162.932.772.662.582.512.462.412.342.272.192.152.112.062.021.971.92
194.383.523.132.902.742.632.542.482.422.382.312.232.162.112.072.031.981.931.88
204.353.493.102.872.712.602.512.452.392.352.282.202.122.082.041.991.951.901.84
214.323.473.072.842.682.572.492.422.372.322.252.182.102.052.011.961.921.871.81
224.303.443.052.822.662.552.462.402.342.302.232.152.072.031.981.941.891.841.78
234.283.423.032.802.642.532.442.372.322.272.202.132.052.011.961.911.861.811.76
244.263.403.012.782.622.512.422.362.302.252.182.112.031.981.941.891.841.791.73
254.243.392.992.762.602.492.402.342.282.242.162.092.011.961.921.871.821.771.71
264.233.372.982.742.592.472.392.322.272.222.152.071.991.951.901.851.801.751.69
274.213.352.962.732.572.462.372.312.252.202.132.061.971.931.881.841.791.731.67
284.203.342.952.712.562.452.362.292.242.192.122.041.961.911.871.821.771.711.65
294.183.332.932.702.552.432.352.282.222.182.102.031.941.901.851.811.751.701.64
304.173.322.922.692.532.422.332.272.212.162.092.011.931.891.841.791.741.681.62
404.083.232.842.612.452.342.252.182.122.082.001.921.841.791.741.691.641.581.51
604.003.152.762.532.372.252.172.102.041.991.921.841.751.701.651.591.531.471.39
1203.923.072.682.452.292.182.092.021.961.911.831.751.661.611.551.501.431.351.25
∞3.843.002.602.372.212.102.011.941.881.831.751.671.571.521.461.391.321.221.00

df₁ = numerator degrees of freedom (columns), df₂ = denominator degrees of freedom (rows). Values are right-tail critical values of F.

Values computed with SciPy and checked against published tables. Free to use and print for teaching. Please link to this page if you share it.

How to read the F table

  1. Pick the table for your α (most often .05) with the buttons above.
  2. Find df₁ across the top. In a one-way ANOVA, df₁ = number of groups − 1. In regression, df₁ = number of predictors.
  3. Find df₂ down the side. In a one-way ANOVA, df₂ = total sample size − number of groups. In regression, df₂ = n − k − 1.
  4. Compare. If your F statistic exceeds the value where they meet, the result is significant.

Worked example

A one-way ANOVA compares 3 teaching methods with 10 students each (N = 30). Then df₁ = 3 − 1 = 2 and df₂ = 30 − 3 = 27. The critical value at α = .05 is 3.35. An observed F(2, 27) = 4.12 exceeds it, so at least one group mean differs, p = .027. Follow up with post hoc tests such as Tukey's HSD.

Where F tests appear

ANOVA and ANCOVA, the overall test of a regression model, comparing nested regression models (the change in R²), and Levene's test for equal variances all use the F distribution.

F = MSbetween / MSwithin

Frequently asked questions

What is the critical F value for df (2, 27) at 0.05?

3.35. For (2, 30) it is 3.32, for (3, 30) it is 2.92 and for (1, 30) it is 4.17.

Which degrees of freedom go first in an F test?

The numerator df (between groups, or model) comes first and the denominator df (within groups, or error) comes second: F(df₁, df₂).

What if my degrees of freedom are not in the F table?

Use the next smaller df₂ in the table for a conservative decision, or enter the exact values in the calculator on this page.

Is the F test one-tailed?

Yes. ANOVA and regression F tests use only the upper tail, because a large F means more variance between groups (or explained by the model) than expected by chance.

What does a large F value mean?

The variance between group means is large relative to the variance within groups. Whether it is significant depends on both degrees of freedom, which is why F must be compared with the critical value or converted to a p-value.

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