Z.TEST(array,x,[sigma])
=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/√n),TRUE)) or 1- Norm.S.Dist ((Average(array)- x) / (STDEV(array)/√n),TRUE).