Calculate the P-value for a z-test.

`Z.TEST(array,x,[sigma])`

- Array - required argument, data or range to test x on
- x - required argument, value to test
- sigma - [OPTIONAL] population standard deviation

`=Z.TEST(A2:A11,4)`

The Z.TEST function can be used to calculate the one-tailed probability-value of a z-test for a data set at a hypothesized population mean. In the example given, the function is used to calculate the one-tailed probability-value of a z-test for the data set in A2:A11 at the hypothesized population mean of 4. This formula returns the value of 0.090574.

`2 * MIN(Z.TEST(A2:A11,4), 1 - Z.TEST(A2:A11,4))`

The Z.TEST function can also be used to calculate the two-tailed probability-value of a z-test for a data set at a hypothesized population mean. In the example given, the function is used to calculate the two-tailed probability-value of a z-test for the data set in A2:A11 at the hypothesized population mean of 4. The formula used is , which returns the value of 0.181148.

`=Z.TEST(A2:A11,6)`

The Z.TEST function can be used to calculate the one-tailed probability-value of a z-test for a data set at a different hypothesized population mean. In the example given, the function is used to calculate the one-tailed probability-value of a z-test for the data set in A2:A11 at the hypothesized population mean of 6. The formula used returns the value of 0.863043.

The Z.TEST function calculates the P-value for a one-tailed z-test, determining the probability that the sample mean is greater than the average of observations in the data set. It returns the #N/A error value if the array argument is empty. The equation for Z.TEST is 1- Norm.S.Dist (((Average(array)-x)/(sigma/âˆšn),TRUE)) or 1- Norm.S.Dist ((Average(array)- x) / (STDEV(array)/âˆšn),TRUE).

- Z.TEST is used to determine the probability that the sample mean is greater than the average of observations in the data set. It returns a one-tailed P-value.
- If the array argument is empty, Z.TEST may return a #N/A error.

The Z.TEST function is a statistical tool used to calculate the P-value of a z-test. It determines the probability that the sample mean would be greater than the average of observations in the data set.

The Z.TEST function can be used in a formula to compute a two-tailed probability value. It can be used to calculate a two-tailed probability that the sample mean is further from x than the average of all the cells in an array.

The Z.TEST represents the probability that the sample mean would be greater than the observed value AVERAGE(array) when the underlying population mean is Î¼0.