In Google Sheets, the function ZTEST is used to perform a one-sample z-test to determine the probability that a sample mean significantly differs from a population mean. It calculates the z-score and the corresponding p-value for the test.

The syntax for the ZTEST function is as follows: ZTEST(datarange, populationmean, [standard_deviation])

datarange: This is the range of cells that contain the sample data for which you want to perform the z-test. populationmean: This represents the hypothesized population mean against which you want to test the sample mean. standard_deviation: This is an optional argument that represents the known or estimated standard deviation of the population. If omitted, the function assumes a standard deviation based on the sample data.

The ZTEST function assumes that the sample data is a simple random sample from a population with a known or estimated standard deviation. It compares the sample mean to the hypothesized population mean to assess whether there is a statistically significant difference.

The ZTEST function calculates the z-score, which measures the number of standard deviations that the sample mean is away from the population mean. It then determines the probability (p-value) associated with the observed z-score.

The p-value represents the probability of obtaining a sample mean as extreme as or more extreme than the observed sample mean, assuming the null hypothesis (that the sample mean is equal to the population mean) is true. A lower p-value indicates stronger evidence against the null hypothesis.