If you have ever run a chi-square test, stared at the output, and wondered, “How do I actually write this up?” — you are not alone. Many students know how to click through SPSS or R, but the reporting sentence is where marks are lost. The good news is that APA style reporting for chi-square is a formula. Once you learn the pattern, you can report any chi-square result confidently, whether it comes from a test of independence or a goodness-of-fit test.
In this guide, you will learn exactly what APA 7th edition expects, see sentence templates you can copy and adapt, work through two fully reported examples, and avoid the most common mistakes examiners notice.
What APA Style Requires for a Chi-Square Result
APA style is about giving the reader everything needed to judge your result, without extra clutter. For a chi-square test, a complete report includes six pieces of information:
- The test statistic, written as the Greek letter chi-square: χ²
- The degrees of freedom, in parentheses right after the symbol
- The sample size, written as N = followed by the total number of cases
- The value of the test statistic itself
- The exact p value (or p < .001 when it is very small)
- An effect size, such as phi (φ) for a 2 × 2 table or Cramér’s V for a larger table
Put together, the basic template looks like this:
χ²(df, N = xxx) = xx.xx, p = .xxx
And with an effect size added:
χ²(df, N = xxx) = xx.xx, p = .xxx, Cramér’s V = .xx
A few formatting rules matter here. APA uses a leading zero for values that can exceed 1, but not for p values, correlations, or effect sizes that cannot exceed 1 — so write p = .007, not p = 0.007, and V = .29, not V = 0.29. Italicise the symbols χ², N, and p, and put a space on either side of the equals sign. Report the chi-square value to two decimal places, and the p value to two or three decimal places.
Step 1: Identify Which Chi-Square Test You Ran
Before you write a single sentence, be clear about which test you used, because the wording changes slightly:
- Chi-square test of independence: used when you want to know whether two categorical variables are associated. Example: Is study preference related to gender?
- Chi-square goodness-of-fit test: used when you want to know whether one categorical variable matches an expected distribution. Example: Do students choose the four study methods equally often, or is one method far more popular?
Naming the test in your sentence helps the reader immediately. Write “A chi-square test of independence showed…” or “A chi-square goodness-of-fit test showed…” rather than just “The test showed…”
Step 2: Gather the Numbers You Need
Open your output and note down these values before you start writing:
- The chi-square value (labelled Pearson Chi-Square in SPSS)
- The degrees of freedom (df)
- The total sample size (N), which is the total number of valid cases, not the number in one group
- The p value (labelled Asymptotic Significance in SPSS)
- The effect size: phi for a 2 × 2 table, Cramér’s V for any larger table
One caution: check the expected cell counts. The chi-square test assumes that most expected frequencies are at least 5. If many cells fall below that, say so in your methods section and consider an alternative such as Fisher’s exact test. Examiners respect a student who notices an assumption problem far more than one who hides it.
Step 3: Write the Result Sentence
Now assemble your sentence using the template. Start with the test name and the finding in plain words, then give the statistics in parentheses or right after the claim. Readers should be able to understand the finding even if they skip the numbers, and check the numbers if they want detail.
Template for a significant test of independence:
“A chi-square test of independence showed a significant association between [Variable A] and [Variable B], χ²(df, N = xxx) = xx.xx, p = .xxx, Cramér’s V = .xx.”
Template for a non-significant result:
“A chi-square test of independence found no significant association between [Variable A] and [Variable B], χ²(df, N = xxx) = xx.xx, p = .xxx.”
For a goodness-of-fit test, the same pattern works:
“A chi-square goodness-of-fit test showed that [the observed distribution] differed significantly from [the expected distribution], χ²(df, N = xxx) = xx.xx, p = .xxx.”
Step 4: Add a Table When It Helps
A short results paragraph is often enough, but a table makes your finding much easier to follow, especially for a thesis. A good chi-square table shows the observed counts (and percentages) for each group, the row and column totals, and a note underneath giving the test statistic, degrees of freedom, sample size, p value, and effect size. Do not repeat every number from the table in your text — use the text to highlight the main pattern, and let the table carry the detail.
Step 5: Interpret, Don’t Just Report
The most common weakness in student write-ups is stopping at the statistics. After the numbers, add one or two sentences explaining what the result means in plain language. Which group was higher? How large is the effect in practical terms? For Cramér’s V, values around .10 are often described as small, around .30 as medium, and around .50 as large, although these are rough guides, not strict cut-offs — always interpret the size in the context of your field.
Worked Example 1: Chi-Square Test of Independence
Imagine a researcher surveys 120 undergraduate students about their preferred study method (group study, solo study, or online videos) and records each student’s gender (female or male). The question is whether study preference is associated with gender.
Suppose the analysis gives: χ²(2, N = 120) = 9.84, p = .007, Cramér’s V = .29.
Here is how to report it in APA style:
“A chi-square test of independence showed a significant association between gender and preferred study method, χ²(2, N = 120) = 9.84, p = .007, Cramér’s V = .29. Female students were more likely than male students to prefer group study, whereas male students were more likely to prefer online videos.”
Notice what this paragraph does: it names the test, states the finding, gives all six required pieces of information, and then interprets the pattern. The degrees of freedom are 2 because the table has 3 rows and 2 columns: (3 − 1) × (2 − 1) = 2. The effect size of .29 suggests a medium-sized association — worth reporting, not just a significant p value.
Worked Example 2: Chi-Square Goodness-of-Fit Test
Now imagine 200 students are asked which of four revision strategies they use most often: flashcards, practice tests, rereading notes, or summarising. If students chose randomly, each strategy would be chosen by about 25% of students. The researcher wants to know whether the observed choices differ from that equal split.
Suppose the analysis gives: χ²(3, N = 200) = 12.40, p = .006.
The APA report could read:
“A chi-square goodness-of-fit test showed that students’ most-used revision strategies differed significantly from an equal distribution across the four strategies, χ²(3, N = 200) = 12.40, p = .006. Practice tests were the most commonly reported strategy, while rereading notes was the least common.”
The degrees of freedom here are 3, because there are four categories: 4 − 1 = 3. No effect size is strictly required for a goodness-of-fit test in every journal, but you may still describe the pattern in words, as above, so the reader can see where the difference lies.
Common Mistakes to Avoid
- Writing p = .000. SPSS displays .000 when the p value is very small, but a p value is never exactly zero. Write p < .001 instead.
- Forgetting the sample size. χ²(2) = 9.84 on its own is incomplete — the reader needs N to judge the result and to compute effect sizes.
- Reporting only the p value. A significant result with a tiny effect size is a very different story from a significant result with a large effect. Always add phi or Cramér’s V for a test of independence.
- Confusing the chi-square value with the p value. The chi-square statistic (for example, 9.84) and the p value (for example, .007) are different numbers with different meanings — never swap them.
- Using the wrong effect size. Use phi only for a 2 × 2 table. For any larger table, use Cramér’s V.
- Writing “the hypothesis was proven.” Statistical tests support or fail to support a hypothesis; they do not prove it. Write “the results supported the hypothesis” instead.
Frequently Asked Questions
Do I report the chi-square value or just the p value?
Report both, plus the degrees of freedom, sample size, and effect size. A p value alone tells the reader almost nothing about the size or nature of the effect.
What if my result is not significant?
Report it exactly the same way, with the full statistics. For example: “A chi-square test of independence found no significant association between gender and preferred study method, χ²(2, N = 120) = 2.31, p = .315.” Non-significant results are still results, and hiding them is poor practice.
Should I write p = .05 or p < .05?
APA prefers exact p values (for example, p = .043) whenever possible. Use p < .001 only when the value is smaller than .001, and use p = .315 style reporting for non-significant values rather than “p > .05” alone.
How do I report chi-square in a table?
Give the observed counts and percentages in the body of the table, and put the full test result — χ²(df, N = xxx) = xx.xx, p = .xxx, effect size — in a note below the table. Keep the table title clear and italicised in APA table format.
Do I need an effect size for a goodness-of-fit test?
It is not always required, but describing the observed pattern in words is essential. If your supervisor or journal asks for an effect size, Cramér’s V can be reported, with the formula and interpretation explained in your methods section.
Final Checklist Before You Submit
Before you hand in your results section, run through this quick check: Did you name the test? Did you give χ², degrees of freedom, N, the test value, the exact p value, and an effect size? Did you interpret the finding in plain language? Did you write p < .001 instead of p = .000? If you can answer yes to all four, your chi-square reporting is in good APA shape — and your examiner will notice the difference.