# Google Sheets CHISQ.TEST Function: Syntax, Examples & Tips - URL: https://betteranalyst.com/google-sheets/chisqtest-function - Author: Better Analyst Formula Bot is now Better Analyst—same account, more powerful analysis.Formula Bot is now Better Analyst—same account and workflows, with more powerful analysis, dashboards, and automation. [Learn what changed](https://betteranalyst.com/formula-bot-is-now-better-analyst) Returns the p-value of a chi-square test comparing observed counts with expected counts. ``` =CHISQ.TEST(observed_range, expected_range) ``` Generate FormulaExplain Formula One free generation or explanation per browser, shared across Excel and Google Sheets. Account usage limits apply afterward. Describe the CHISQ.TEST you need in plain EnglishGenerate Formula ## Parameters | Parameter | Required | Description | | - | - | - | | **observed\_range** | Yes | The observed counts. Can be a single row, a single column, or a table. | | **expected\_range** | Yes | The expected counts under the null hypothesis. Must be the same size and shape as **observed\_range**. | ## What Is CHISQ.TEST? CHISQ.TEST runs a Pearson chi-square test in a single formula. You supply the counts you observed and the counts you expected, and it returns the **p-value**: the probability of seeing differences at least this large if the null hypothesis were true. A small p-value (commonly below 0.05) suggests the observed pattern is unlikely to be due to chance alone. CHISQ.TEST is the modern name for [CHITEST](https://betteranalyst.com/google-sheets/chitest-function); both behave the same way. ## How CHISQ.TEST Works You give CHISQ.TEST two ranges of the same size: - **observed\_range**: the counts you actually recorded - **expected\_range**: the counts you would expect if the null hypothesis were true CHISQ.TEST calculates the chi-square statistic, the sum of (observed − expected)² ÷ expected over every cell, and converts it to a right-tailed p-value. Degrees of freedom are worked out from the shape of the ranges: - A single row or single column of *n* cells uses *n* − 1 degrees of freedom (goodness-of-fit). - A table with *r* rows and *c* columns, where both are greater than 1, uses (*r* − 1) × (*c* − 1) (test of independence). The result is the p-value only. CHISQ.TEST does not return the statistic itself. ## Basic Examples ### Goodness-of-fit Observed counts of 30 and 20 in B2:B3, with expected counts of 25 and 25 in C2:C3: ``` =CHISQ.TEST(B2:B3, C2:C3) ``` The statistic is (5² ÷ 25) + (5² ÷ 25) = 2 with 1 degree of freedom, so the result is about 0.157. A 60/40 split in 50 trials is not strong evidence against an even split. ### Test of independence in a table With observed counts in B2:D3 (2 rows × 3 columns), build the expected table in G2:I3 using row and column totals: ``` =SUM($B2:$D2) * SUM(B$2:B$3) / SUM($B$2:$D$3) ``` Fill that formula across G2:I3, then: ``` =CHISQ.TEST(B2:D3, G2:I3) ``` This returns the p-value with (2 − 1) × (3 − 1) = 2 degrees of freedom. ### Even distribution across categories ``` =CHISQ.TEST(B2:B8, ARRAYFORMULA(B2:B8*0 + SUM(B2:B8)/7)) ``` Tests whether counts for the seven days of the week are spread evenly, generating the expected counts inline. ### Labelling the result ``` =IF(CHISQ.TEST(B2:D3, G2:I3) < 0.05, "Related", "No evidence of a relationship") ``` ## Getting the Statistic Too If you also want to report the chi-square statistic, calculate it alongside the p-value: ``` =SUMPRODUCT((B2:D3-G2:I3)^2/G2:I3) ``` Feed it to CHISQ.DIST.RT with the degrees of freedom and you will get the same p-value that CHISQ.TEST returns. ## Common Use Cases - **A/B testing**: are conversion counts independent of the variant shown? - **Survey analysis**: does preference differ by region, age group, or plan? - **Quality**: are defects spread evenly across shifts or machines? - **Marketing**: does channel mix differ between new and returning customers? ## Common Errors - **#N/A or an error from mismatched ranges**: The observed and expected ranges must be the same size and shape. - **Expected counts of zero**: Division by zero makes the test impossible. Combine sparse categories. - **Passing percentages instead of counts**: Both ranges should be counts. Expected values in proportions understate the statistic. - **Expected totals not matching**: Expected counts should add up to the same total as the observed counts. - **Small samples**: When many expected counts are below about 5, the chi-square approximation is unreliable. ## Tips and Best Practices - Build expected counts with formulas rather than typing them, so they update with the data. - Report the p-value together with the statistic and degrees of freedom. - A small p-value says the variables are related, not how strongly. Look at the table itself to see where the differences are. ## Related Functions - [CHITEST](https://betteranalyst.com/google-sheets/chitest-function): legacy chi-square test - [CHISQ.DIST.RT](https://betteranalyst.com/google-sheets/chisqdistrt-function): right-tailed probability (p-value) - [CHISQ.INV.RT](https://betteranalyst.com/google-sheets/chisqinvrt-function): critical value from a right-tail probability - [CHISQ.DIST](https://betteranalyst.com/google-sheets/chisqdist-function): left-tailed probability or density - [IF](https://betteranalyst.com/google-sheets/if-function): turn a p-value into a decision ## Example use case A product manager shows two onboarding flows to new users and records whether each user activated. With a 2×2 table of counts and an expected table built from row and column totals, =CHISQ.TEST(B2:C3, F2:G3) returns a p-value of 0.01, indicating activation depends on the flow. ## Need more help with Google Sheets formulas? 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[Create Free Account](https://betteranalyst.com/signup)[Try Formula Generator](https://betteranalyst.com/excel-ai) ## Google Sheets how-to guides - [How To Count Unique Values In Google Sheets](https://betteranalyst.com/google-sheets/how-to-count-unique-values-in-google-sheets) - [How To Create A Pivot Table In Google Sheets](https://betteranalyst.com/google-sheets/how-to-create-a-pivot-table-in-google-sheets) - [How To Divide In Google Sheets](https://betteranalyst.com/google-sheets/how-to-divide-in-google-sheets) - [How To Enable Macros In Google Sheets](https://betteranalyst.com/google-sheets/how-to-enable-macros-in-google-sheets) - [How To Filter In Google Sheets](https://betteranalyst.com/google-sheets/how-to-filter-in-google-sheets) - [How To Find Circular References In Google Sheets](https://betteranalyst.com/google-sheets/how-to-find-circular-references-in-google-sheets) - [How To Find Duplicates In Google Sheets](https://betteranalyst.com/google-sheets/how-to-find-duplicates-in-google-sheets) - [How To Freeze A Row In Google Sheets](https://betteranalyst.com/google-sheets/how-to-freeze-a-row-in-google-sheets) ## Explore all Google Sheets formulas Browse our complete library of Google Sheets formula guides Compare your options ## Decide with evidence, not a sales pitch. 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