The F-table gives critical values of the F-distribution, used in ANOVA and to compare variances. Rows are the denominator degrees of freedom (df₂), columns the numerator degrees of freedom (df₁). Two tables are shown for the two most common significance levels.

Example: a one-way ANOVA with df₁ = 3, df₂ = 20 at α = 0.05 → critical F = 3.10. Reject H₀ if your F-statistic exceeds this.

α = 0.05

df₂ \ df₁12345678910121520243060
1161.45199.50215.71224.58230.16233.99236.77238.88240.54241.88243.91245.95248.01249.05250.10252.20
218.5119.0019.1619.2519.3019.3319.3519.3719.3819.4019.4119.4319.4519.4519.4619.48
310.139.559.289.129.018.948.898.858.818.798.748.708.668.648.628.57
47.716.946.596.396.266.166.096.046.005.965.915.865.805.775.755.69
56.615.795.415.195.054.954.884.824.774.744.684.624.564.534.504.43
65.995.144.764.534.394.284.214.154.104.064.003.943.873.843.813.74
75.594.744.354.123.973.873.793.733.683.643.573.513.443.413.383.30
85.324.464.073.843.693.583.503.443.393.353.283.223.153.123.083.01
95.124.263.863.633.483.373.293.233.183.143.073.012.942.902.862.79
104.964.103.713.483.333.223.143.073.022.982.912.852.772.742.702.62
114.843.983.593.363.203.093.012.952.902.852.792.722.652.612.572.49
124.753.893.493.263.113.002.912.852.802.752.692.622.542.512.472.38
134.673.813.413.183.032.922.832.772.712.672.602.532.462.422.382.30
144.603.743.343.112.962.852.762.702.652.602.532.462.392.352.312.22
154.543.683.293.062.902.792.712.642.592.542.482.402.332.292.252.16
164.493.633.243.012.852.742.662.592.542.492.422.352.282.242.192.11
174.453.593.202.962.812.702.612.552.492.452.382.312.232.192.152.06
184.413.553.162.932.772.662.582.512.462.412.342.272.192.152.112.02
194.383.523.132.902.742.632.542.482.422.382.312.232.162.112.071.98
204.353.493.102.872.712.602.512.452.392.352.282.202.122.082.041.95
244.263.403.012.782.622.512.422.362.302.252.182.112.031.981.941.84
304.173.322.922.692.532.422.332.272.212.162.092.011.931.891.841.74
404.083.232.842.612.452.342.252.182.122.082.001.921.841.791.741.64
604.003.152.762.532.372.252.172.102.041.991.921.841.751.701.651.53
1203.923.072.682.452.292.182.092.021.961.911.831.751.661.611.551.43

α = 0.01

df₂ \ df₁12345678910121520243060
14052.184999.505403.355624.585763.655858.995928.365981.076022.476055.856106.326157.286208.736234.636260.656313.03
298.5099.0099.1799.2599.3099.3399.3699.3799.3999.4099.4299.4399.4599.4699.4799.48
334.1230.8229.4628.7128.2427.9127.6727.4927.3527.2327.0526.8726.6926.6026.5026.32
421.2018.0016.6915.9815.5215.2114.9814.8014.6614.5514.3714.2014.0213.9313.8413.65
516.2613.2712.0611.3910.9710.6710.4610.2910.1610.059.899.729.559.479.389.20
613.7510.929.789.158.758.478.268.107.987.877.727.567.407.317.237.06
712.259.558.457.857.467.196.996.846.726.626.476.316.166.075.995.82
811.268.657.597.016.636.376.186.035.915.815.675.525.365.285.205.03
910.568.026.996.426.065.805.615.475.355.265.114.964.814.734.654.48
1010.047.566.555.995.645.395.205.064.944.854.714.564.414.334.254.08
119.657.216.225.675.325.074.894.744.634.544.404.254.104.023.943.78
129.336.935.955.415.064.824.644.504.394.304.164.013.863.783.703.54
139.076.705.745.214.864.624.444.304.194.103.963.823.663.593.513.34
148.866.515.565.044.694.464.284.144.033.943.803.663.513.433.353.18
158.686.365.424.894.564.324.144.003.893.803.673.523.373.293.213.05
168.536.235.294.774.444.204.033.893.783.693.553.413.263.183.102.93
178.406.115.184.674.344.103.933.793.683.593.463.313.163.083.002.83
188.296.015.094.584.254.013.843.713.603.513.373.233.083.002.922.75
198.185.935.014.504.173.943.773.633.523.433.303.153.002.922.842.67
208.105.854.944.434.103.873.703.563.463.373.233.092.942.862.782.61
247.825.614.724.223.903.673.503.363.263.173.032.892.742.662.582.40
307.565.394.514.023.703.473.303.173.072.982.842.702.552.472.392.21
407.315.184.313.833.513.293.122.992.892.802.662.522.372.292.202.02
607.084.984.133.653.343.122.952.822.722.632.502.352.202.122.031.84
1206.854.793.953.483.172.962.792.662.562.472.342.192.031.951.861.66

Computed with SciPy (f.ppf). Run a full analysis with the One-Way ANOVA Calculator.

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