NORMSINV
The NORMSINV function returns the inverse of the standard normal cumulative distribution. It calculates the Z-score corresponding to a specified probability in a standard normal distribution.
Syntax 🔗
=NORMSINV(Probability)
Probability | The probability for which you want to find the corresponding Z-score. Should be between 0 and 1 inclusive. |
About NORMSINV 🔗
The NORMSINV function in Excel helps you find the Z-score corresponding to a specific probability in a standard normal distribution. This function is useful when you need to determine where a value falls within a dataset that has a mean of 0 and a standard deviation of 1.
To use NORMSINV, enter a probability value between 0 and 1. Excel will calculate the Z-score that matches this probability, allowing you to interpret data points in terms of the standard normal distribution.
With NORMSINV, you can assess how unusual or typical a value is within a dataset. Use this function to analyze the likelihood of an event based on its position in the normal distribution curve, supporting your statistical evaluations.
Examples 🔗
To find the Z-score for a probability of 0.95, use the NORMSINV formula as follows:
=NORMSINV(0.95)
This formula returns the Z-score for a probability of 0.95 in a standard normal distribution.
Notes 🔗
Enter a valid probability value between 0 and 1 in the NORMSINV function. The result indicates the number of standard deviations away from the mean in a standard normal distribution.
Questions 🔗
The NORMSINV function calculates the Z-score that corresponds to a given probability in a standard normal distribution. It helps in determining the position of a value within the distribution in terms of standard deviations from the mean.
What is the range of valid probabilities for the NORMSINV function?The NORMSINV function requires a probability value between 0 and 1. This represents the likelihood of an event occurring within the context of a standard normal distribution.
How can I utilize the Z-score obtained from NORMSINV?The Z-score obtained from NORMSINV helps in understanding the relative position of a data point in a normal distribution. Positive Z-scores denote values above the mean, while negative Z-scores indicate values below the mean.