الحد الأقصى للمنازل العشرية: 6؛ إلى الأقرب، وعند التعادل بعيدًا عن الصفر
Decision
Fail to reject H₀
χ² statistic
3.8
Degrees of freedom
5
Critical value
11.0705
Smallest expected count
20
Fail to reject H₀ at α = 0.05. If every category were equally likely, a result at least this extreme would turn up with probability 0.5786. The p-value is not the probability that H₀ is true, and not rejecting H₀ does not show it is true — the sample may be too small to detect a real effect. The largest contribution comes from category 1 (observed 15, expected 20).
p-value area under χ² with 5 df
χ² contribution per category, observed vs expected (blue: above, orange: below)
Observed, expected and contribution to χ² الصفوف: 6
Category
Observed
Expected
(O − E)²/E
1
15
20
1.25
2
22
20
0.2
3
18
20
0.2
4
25
20
1.25
5
17
20
0.45
6
23
20
0.45
طريقة الحساب S
Hypotheses
H0:counts follow the equal proportions,H1:they don’t
Expected counts
Ei=N∑wwi⇒E=(20,20,20,20,20,20)
Statistic
χ2=∑E(O−E)2=1.25+0.2+0.2+1.25+0.45+0.45=3.8
Degrees of freedom
ν=k−1−m=5
p-value
p=P(χ52≥3.8)=0.57855529
Decision
p>α=0.05⇒do not reject H0
Equivalently, compare χ² with the critical value 11.0705.
حول Chi-square test calculator
Pearson's chi-square test compares observed counts with the counts a hypothesis predicts: χ² = Σ(O − E)²/E. The goodness-of-fit test takes the expected counts from equal or given proportions and has k − 1 degrees of freedom, one fewer for each parameter estimated from the data. The test of independence sets E = row total × column total ÷ grand total for each cell of a contingency table and has (r − 1)(c − 1) degrees of freedom.
It answers questions such as whether a die is fair or whether a preference depends on region. The default 120 rolls (15, 22, 18, 25, 17, 23) give χ² = 3.8 on 5 df and p = 0.579, far below the 11.07 needed at α = 0.05, so the counts are consistent with a fair die.
The χ² approximation needs expected counts of about 5 or more. Cramér's V, from 0 to 1, measures how strong an association in a table is.
أمثلة محلولة
Is the die fair? (defaults)
Test
Goodness of fit
Observed counts
15, 22, 18, 25, 17, 23
Expected distribution
Equal in every category
Significance level α
0.05
χ² statistic
3.8
Degrees of freedom
5
p-value
0.578555
Decision
Fail to reject H₀
Critical value
11.0705
مصدر التحقق: χ² by hand: Σ(O − 20)²/20 = 76/20; p from the A&S 26.4.4 closed form for odd ν (pyref.chi2_sf_int); χ²₀.₉₅,₅ = 11.070 (χ² table)
Mendel's peas vs 9:3:3:1
Test
Goodness of fit
Observed counts
315 108 101 32
Expected distribution
Given ratios or counts
Expected ratios or counts
9 3 3 1
Significance level α
0.05
χ² statistic
0.470024
Degrees of freedom
3
p-value
0.925426
مصدر التحقق: Classic textbook example (χ² ≈ 0.47, p ≈ 0.93); exact χ² with Python fractions, p from A&S 26.4.4
2×2 table
Test
Independence
Contingency table
20 30
30 20
Significance level α
0.05
χ² statistic
4
Degrees of freedom
1
p-value
0.0455
Cramér's V
0.2
مصدر التحقق: All E = 25, χ² = 4·25/25 = 4; p = erfc(√2) = 0.0455003 (Python math.erfc); V = √(4/100)
2×3 table (defaults)
Test
Independence
Contingency table
42 33 25
28 37 35
Significance level α
0.05
χ² statistic
4.695238
Degrees of freedom
2
p-value
0.095597
مصدر التحقق: Expected counts R·C/N and χ² with Python fractions; p = e^(−χ²/2) for ν = 2 (A&S 26.4.5)
الأسئلة
What does the chi-square p-value mean?
It is the probability of a χ² statistic at least as large as the one observed if the null hypothesis holds, such as a fair die or independent rows and columns. For the default rolls p = 0.579: a fair die would give counts at least this uneven in about 58% of 120-roll experiments. A large p-value does not prove the die fair, since small samples can miss a real bias.
What is the minimum expected count for a chi-square test?
Cochran's (1954) rule asks that no expected count be below 1 and no more than 20% of cells be below 5. When it fails, merge sparse categories or, for a 2×2 table, use Fisher's exact test. The rule is about expected counts, not observed ones: an observed 0 is fine when its expected count is 5 or more. The warning here appears whenever any expected count is below 5.
How do you find the degrees of freedom for a chi-square test?
For goodness of fit, df = k − 1 − m, where k is the number of categories and m the number of parameters estimated from the data, so a six-sided die gives 5. For independence, df = (rows − 1) × (columns − 1): 2 for a 2×3 table and 1 for a 2×2 table. The 5% critical values for 1, 2 and 5 df are 3.841, 5.991 and 11.070.
What is Cramér's V?
Cramér's V = √(χ² / (N × (min(r, c) − 1))) rescales χ² to a 0-to-1 strength of association that does not grow with the sample size. The 2×2 worked example, χ² = 4 with N = 100, gives V = 0.2. Cohen (1988) treats 0.1, 0.3 and 0.5 as small, medium and large for a 2×2 table; tables with more rows and columns have lower thresholds.
Can I use percentages instead of counts?
No. χ² grows in proportion to the sample size, so the same percentages from 1,000 observations give 10 times the χ² of 100 observations. Entering percentages treats the sample as exactly 100 and gives the wrong p-value for any other sample size. Expected ratios, by contrast, can be on any scale: 9 3 3 1 is rescaled to the observed total.
ما مدى دقة «Chi-square test calculator»؟
تعتمد الدقة على مدخلاتك وافتراضات الطريقة. يستخدم الحساب العشري 50 رقمًا معنويًا، لكن التقديرات والأساليب العددية وبيانات المصدر قد تكون أقل دقة؛ تقريب القيم المعروضة لا يزيل هذه الحدود. أمثلة محلولة جرى التحقق منها بمصادر مستقلة: 5. مثلًا، يجري التحقق من «Is the die fair? (defaults)» بالرجوع إلى χ² by hand: Σ(O − 20)²/20 = 76/20; p from the A&S 26.4.4 closed form for odd ν (pyref.chi2_sf_int); χ²₀.₉₅,₅ = 11.070 (χ² table).
ما مصدر هذه الطريقة؟
NIST/SEMATECH e-Handbook of Statistical Methods, §1.3.5.15 Chi-square goodness-of-fit test; NIST/SEMATECH e-Handbook, §7.4.5 contingency tables / test of independence; Abramowitz & Stegun, Handbook of Mathematical Functions, §26.4 (χ² probability function).