# NORM.S.INV

## Y ## Understanding the NORM.S.INV Function

The NORM.S.INV function is a statistical function in Power BI that returns the inverse of the standard normal cumulative distribution for a given probability. In simpler terms, it allows you to calculate the z-score for a given probability. The NORM.S.INV function takes only one argument, which is the probability for which you want to calculate the inverse standard normal distribution. For example, if you want to find the z-score for a probability of 0.95, you would use the NORM.S.INV function.

## How to Use the NORM.S.INV Function in Power BI

Using the NORM.S.INV function in Power BI is quite easy. First, create a new measure in your report by going to the “Modeling” tab and clicking on “New Measure”. Next, type in the following formula:

NORM.S.INV( probability )

``` Replace "probability" with the actual probability for which you want to calculate the inverse standard normal distribution. For example, if you want to find the z-score for a probability of 0.95, your formula would look like this: ```

NORM.S.INV( 0.95 )

``` Once you have typed in your formula, give your measure a name and click "Enter". Your new measure will now be available in the "Fields" pane and can be used in your report visuals. Examples of Using the NORM.S.INV Function Let's take a look at some examples of how to use the NORM.S.INV function in Power BI. Example 1: Calculating the Z-Score for a Given Probability Suppose you have a dataset that contains the heights of a sample of individuals. You want to find the z-score for a person who is 6 feet tall, assuming the mean height of the population is 5 feet 6 inches and the standard deviation is 2 inches. To do this, you would use the following formula: ```

(NORM.S.INV( (6*12-5.5*12)/(2) ))

``` This formula takes the person's height, subtracts the mean height, and divides by the standard deviation to get the z-score. The NORM.S.INV function then takes this z-score and calculates the inverse standard normal distribution. The result of this formula is the z-score for a person who is 6 feet tall. Example 2: Calculating the Confidence Interval for a Given Sample Mean Suppose you have a dataset that contains the weights of a sample of students. You want to find the 95% confidence interval for the population mean weight, assuming the sample mean weight is 150 pounds and the standard deviation is 10 pounds. To do this, you would use the following formula: ```

150 + (NORM.S.INV(0.975)*10/SQRT(100))

``` This formula takes the sample mean weight, adds and subtracts the margin of error calculated using the NORM.S.INV function, and returns the confidence interval. The result of this formula is the confidence interval for the population mean weight with a 95% confidence level. Using the NORM.S.INV function in Power BI can save you time and effort when performing complex statistical calculations. It allows you to easily calculate the inverse standard normal distribution for a given probability and can be used in a variety of scenarios, from calculating confidence intervals to finding z-scores. We hope this article has helped you understand how the NORM.S.INV function works and provided some examples of how to use it in your Power BI reports. Power BI DAX Training Courses by G Com Solutions (0800 998 9248) Power BI DAX Intensive Training Course £1,050.00 – £26,550.00 Select optionsContinue Loading Done Power BI DAX Introduction £395.00 – £9,750.00 Select optionsContinue Loading Done Power BI DAX Intermediate £395.00 – £9,750.00 Select optionsContinue Loading Done Power BI DAX Advanced £395.00 – £9,750.00 Select optionsContinue Loading Done Upcoming Courses 6-8 Jun 23 (London or Online)8-10 Aug 23 (London or Online)24-26 Oct 23 (London or Online) Contact Us Subject Your Name (required) Company/Organisation Email (required) Telephone Training Course(s) Power BI Intensive TrainingPower BI introduction Power BI IntermediatePower BI AdvancedDAXPower Query MPower BI CertificationPower BI AdministrationPower PlatformPower AutomatePower AppsOTHER Your Message Upload Example Document(s) (Zip multiple files) ```
``` ```
``` ```
``` ```
``` ```
``` ```