# Z.TEST

The `Z.TEST` formula returns the probability of a certain value occurring in a normal distribution. This formula is commonly used to test whether two samples have the same mean by comparing their Z scores. The formula returns a value between 0 and 1, with a result closer to 1 indicating a higher likelihood that the value could occur by chance.

## Usage

Use the `Z.TEST` formula with the syntax shown below, it has 2 required parameters and 1 optional parameter:

Parameters:
1. data (required):
The range of cells or array containing the data to be tested.
2. value (required):
The value to be tested.
3. standard_deviation (optional):
An optional parameter representing the population standard deviation. If not provided, the sample standard deviation will be used instead.

## Examples

Here are a few example use cases that explain how to use the `Z.TEST` formula in Google Sheets.

### Testing for significant differences in sample means

By using the `Z.TEST` formula, you can quickly test whether two samples have significantly different means.

### Determining the probability of a value occurring in a normal distribution

You can use `Z.TEST` to determine the probability of a given value occurring in a normal distribution with a known mean and standard deviation.

### Testing for the significance of correlation coefficients

The `Z.TEST` formula can also be used to test whether the correlation coefficient between two variables is significantly different from zero.

## Common Mistakes

`Z.TEST` not working? Here are some common mistakes people make when using the `Z.TEST` Google Sheets Formula:

### Using incorrect data range

One common mistake when using the `Z.TEST` function is using an incorrect range of data, such as including blank cells or non-numeric values in the range.

### Incorrectly specifying standard deviation

Another common mistake is incorrectly specifying the standard deviation of the population, such as using the standard deviation of the sample instead of the known standard deviation.

### Confusing one-tailed and two-tailed tests

A common mistake when using the `Z.TEST` function is confusing one-tailed and two-tailed tests, which can result in incorrect calculations of statistical significance.

The following functions are similar to `Z.TEST` or are often used with it in a formula:

• `T.TEST`

The `T.TEST` function calculates the probability associated with a Student's t-test. This function is commonly used in statistics to determine whether two samples are likely to have come from the same two underlying populations that have the same mean. It returns the probability that the two samples are different. The function assumes that the two samples are independent of each other and have equal variances.

• `CHISQ.TEST`

The `CHISQ.TEST` formula calculates the test for independence of two categorical ranges of data using the chi-squared distribution. It returns the probability that any observed differences between the two ranges are due to chance. This formula is commonly used in hypothesis testing to determine whether there is a significant association between two variables.

• `CORREL`

The `CORREL` formula returns the correlation coefficient between two sets of data. This coefficient represents the strength of the linear relationship between the two sets of data, with values ranging from -1 (perfect negative correlation) to 1 (perfect positive correlation).

• `STDEV`

The `STDEV` function calculates the standard deviation of a set of numbers. It measures the amount of variation or dispersion of a set of values from the average (mean) value. It is commonly used in statistics to determine the spread of a data set. The values can be supplied as individual cells, ranges, or constants.

You can learn more about the `Z.TEST` Google Sheets function on Google Support.