In Excel: use the appropriate test function, such as =T.TEST(array1,array2,2,2) for a two-tailed two-sample t-test, and interpret the result against your chosen alpha level.
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Choose the statistical test before writing the formula.
Put each sample in a clean numeric range.
Use the matching Excel test function and tail/type arguments.
Report p-value with sample sizes and the test used.
Need it as an auditable file?
Ships inside the linked template — formula-driven, unlocked, audit-ready.
What this does
A p-value is not a generic spreadsheet statistic; it comes from a specific hypothesis test. Excel can calculate p-values with T.TEST, Z.TEST, CHISQ.TEST and Data Analysis ToolPak outputs. The right function depends on the design, distribution assumptions and whether the test is one-tailed or two-tailed. Keep the inputs visible and clearly labelled and the whole thing stays auditable — anyone who opens the file later, including you, can see at a glance exactly what feeds the result and change one assumption without hunting through the formula. The difference between a quick fix and a sheet you can trust is the extra minute you spend validating “determine p value in excel”. Start on a copy or a tiny sample, keep the affected cells visible, and compare the result with the tool above before you touch the real workbook. When a formula is involved, keep the inputs labelled beside it, reference cells instead of typing values, and apply number formatting only after the result checks out. The point is a calculation you can defend to a CFO or an auditor, but the practical win is that someone else can open the file and understand what happened without asking you.
A worked example
Scores before training are in A2:A21 and after training in B2:B21 for separate groups. =T.TEST(A2:A21,B2:B21,2,2) returns the two-tailed p-value for a two-sample equal-variance t-test. If p is 0.03 and alpha is 0.05, the difference is statistically significant under that test. P-value content needs caution because users can easily produce a number that looks authoritative but comes from the wrong test. One habit worth forming early: name the cells that hold your inputs, so the formula reads in plain language instead of a string of cell addresses. A reviewer — or you in three months — can then follow the logic without decoding what B7 and D2 were supposed to mean, which is most of what makes a sheet maintainable.
In Google Sheets
Google Sheets handles this almost identically to Excel. The formula syntax above is the same, and the menu lives under a slightly different label rather than a ribbon tab. Use the platform toggle at the top of the page to switch every keyboard shortcut between Windows and Mac, and expect at most cosmetic differences in naming. Keep this page bookmarked for the next time the same question comes up. Better still, repeat the steps once in your own workbook — doing it yourself is what turns a copied answer into something you remember. Treat “determine p value in excel” as a small building block rather than a chore. Once the inputs sit in their own cells and the formula reads from them, the same setup answers a dozen related questions with a tweak, and Excel keeps every dependent figure current as the data changes. The tool above is there so you can rehearse and verify before committing anything to a real workbook; the steps and worked example are there so the logic sticks. Get it right once and it stops costing you time — it starts saving it, every time the question comes back around.
Common mistakes
- Using
T.TESTfor every p-value question. - Ignoring paired versus unpaired samples.
- Treating p-value as effect size.
- Changing one-tailed versus two-tailed after seeing results.
Frequently asked questions
Which Excel function gives a p-value?
It depends on the test: T.TEST, Z.TEST, CHISQ.TEST and ToolPak tests can return p-values.
Is p < 0.05 always significant?
Only relative to a prechosen alpha and suitable test assumptions.
Does p-value show importance?
No. It is evidence against a null hypothesis, not effect size.