This article describes the formula syntax and usage of the Z. For a given hypothesized population mean, x, Z. TEST 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.
To see how Z. TEST can be used in a formula to compute a two-tailed probability value, see the Remarks section below. Array Required. The array or range of data against which to test x. Sigma Optional. The population known standard deviation. If omitted, the sample standard deviation is used. Important: This function has been replaced with one or more new functions that may provide improved accuracy and whose names better reflect their usage.
Although this function is still available for backward compatibility, you should consider using the new functions from now on, because this function may not be available in future versions of Excel. For more information about the new function, see Z.
TEST function. Array Required. The array or range of data against which to test x. Sigma Optional. The population known standard deviation. If omitted, the sample standard deviation is used. Copy the example data in the following table, and paste it in cell A1 of a new Excel worksheet. Start Your Free Excel Course. If we have given one dataset, then we use the Z TEST function, which falls under the statistical functions category. This function gives you the probability that the supplied hypothesized sample mean is greater than the mean of the supplied data values.
The formula is given below for calculating the two-tailed P-value of a Z TEST for the given hypothesized population, which is 5. Now we need to calculate the variance of both subjects so that we will use the below formula for this:.
However, these simple conditions and the corresponding hypothesis test are sometimes encountered early in a statistics class. After learning the process of a hypothesis test, these conditions are relaxed in order to work in a more realistic setting. The particular hypothesis test we consider has the following form:. We see that steps two and three are computationally intensive compared two steps one and four.
The Z. TEST function will perform these calculations for us. TEST function does all of the calculations from steps two and three above. It does a majority of the number crunching for our test and returns a p-value.
There are three arguments to enter into the function, each of which is separated by a comma. The following explains the three types of arguments for this function.
There are a few things that should be noted about this function:. We suppose that the following data are from a simple random sample of a normally distributed population of unknown mean and standard deviation of More formally, we have the following hypotheses:.
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