Use the appropriate Excel function for your test
For a t-test, use `=T.TEST(array1,array2,tails,type)`
For a z-test, use `=Z.TEST(array,x,[sigma])`
For a chi-square test, use `=CHISQ.TEST(actual_range,expected_range)`
For an F-test, use `=F.TEST(array1,array2)`
For a correlation significance test, calculate the test statistic first, then use the relevant distribution function
For a one-sample t-test, compute the t statistic and use `=T.DIST.2T(ABS(t),df)` for a two-tailed p value
For a one-tailed t test, use `=T.DIST.RT(t,df)` or `=T.DIST(t,df,TRUE)` depending on the tail
For a z statistic, use `=NORM.S.DIST(z,TRUE)` for left-tailed p values
For a right-tailed z p value, use `=1-NORM.S.DIST(z,TRUE)`
For a two-tailed z p value, use `=2*(1-NORM.S.DIST(ABS(z),TRUE))`
For ANOVA, use the p value from the ANOVA output table in the Data Analysis ToolPak
Enable the Data Analysis ToolPak from `File` > `Options` > `Add-ins` > `Analysis ToolPak`
Open `Data` > `Data Analysis` and choose the relevant test
Read the p value from the output table labeled `P(T<=t)`, `P(Z<=z)`, `P(F<=f)`, or `P-value`
Use `=CHISQ.DIST.RT(chisq,df)` for a right-tailed chi-square p value
Use `=F.DIST.RT(f,df1,df2)` for an F-test p value
Use `=T.TEST` for direct p value output without manually calculating the test statistic
Match the tail type in Excel to your hypothesis test
Use absolute values for two-tailed p value formulas when required