Edit

Share via


WorksheetFunction.ZTest(Object, Double, Object) Method

Definition

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.

public double ZTest (object Arg1, double Arg2, object Arg3);
Public Function ZTest (Arg1 As Object, Arg2 As Double, Optional Arg3 As Object) As Double

Parameters

Arg1
Object

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

Arg2
Double

The value to test.

Arg3
Object

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

Returns

Remarks

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(Object, Double, Object) method.

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

ZTest is calculated as follows when sigma is not omitted:

Figure 1: Equation for ZTest when sigma is not omitted

or when sigma is omitted:

Figure 2: Equation for ZTest when sigma is omitted

where 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 μ0. From the symmetry of the Normal distribution, if AVERAGE(array) < μ0, 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 μ0 (in either direction) than AVERAGE(array), when the underlying population mean is μ0:=2 * MIN(ZTEST(array,μ0,sigma), 1 - ZTEST(array,μ0,sigma)).

Applies to