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WorksheetFunction.ZTest Method (Excel)

Returns the one-tailed probability-value of a z-test. For a given hypothesized population mean, ZTEST returns the probability that the sample mean would be greater than the average of observations in the data set (array) — that is, the observed sample mean.


Important note Important

This function has been replaced with one or more new functions that may provide improved accuracy and whose names better reflect their usage. This function is still available for compatibility with earlier versions of Excel. However, if backward compatibility is not required, you should consider using the new functions from now on, because they more accurately describe their functionality.

For more information about the new function, see the Z_Test method.

expression .ZTest(Arg1, Arg2, Arg3)

expression A variable that represents a WorksheetFunction object.

Parameters

Name

Required/Optional

Data Type

Description

Arg1

Required

Variant

Array is the array or range of data against which to test the hypothesized population mean.

Arg2

Required

Double

The value to test.

Arg3

Optional

Variant

Sigma - the population (known) standard deviation. If omitted, the sample standard deviation is used.

Return Value

Double

  • If array is empty, ZTEST returns the #N/A error value.

  • ZTEST is calculated as follows when sigma is not omitted: Ff195317.awfztest_ZA06051270(en-us,office.14).gifor when sigma is omitted: Ff195317.awfztsta_ZA06054798(en-us,office.14).gifwhere x is the sample mean AVERAGE(array); s is the sample standard deviation STDEV(array); and n is the number of observations in the sample COUNT(array).

  • ZTEST represents the probability that the sample mean would be greater than the observed value AVERAGE(array), when the underlying population mean is μ 0 . From the symmetry of the Normal distribution, if AVERAGE(array) < μ 0 , ZTEST will return a value greater than 0.5.

  • The following Excel formula can be used to calculate the two-tailed probability that the sample mean would be further from μ 0 (in either direction) than AVERAGE(array), when the underlying population mean is μ 0 : =2 * MIN(ZTEST(array,μ 0 ,sigma), 1 - ZTEST(array,μ 0 ,sigma)).

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