GAUSS
The GAUSS function returns the probability that a standard normal random variable is less than a specified value. It calculates the area under the normal distribution curve to the left of the given number. Use it to assess probabilities in a normal distribution model.
Syntax 🔗
=GAUSS(Z)
Z | The value at which to evaluate the standard normal distribution. |
About GAUSS 🔗
Use the GAUSS function in Excel to find the probability of a value occurring within a standard normal distribution. This function helps you quickly calculate the probability for statistical analysis and decision-making. It's useful for tasks like risk assessment, quality control, or hypothesis testing, providing a simple way to assess probabilities within a standard normal distribution.
Examples 🔗
To find the probability of a value occurring within a standard normal distribution with a Z-score of 1.5, use the formula: =GAUSS(1.5)
To calculate the probability of a Z-score of -0.75 occurring within a standard normal distribution, use: =GAUSS(-0.75)
Notes 🔗
Use the GAUSS function to find the cumulative distribution function for a standard normal distribution. Input a Z-score to get the cumulative probability from the mean to your specified Z-score on the distribution curve.
Questions 🔗
The output of the GAUSS function signifies the cumulative probability of a specified value occurring in a standard normal distribution.
Can the GAUSS function be used for non-standard normal distributions?No, the GAUSS function is specifically designed for standard normal distributions where the mean is 0 and the standard deviation is 1. For non-standard normal distributions, you may need to apply additional transformations or consider other statistical functions.
How precise are the results provided by the GAUSS function?The results offered by the GAUSS function are based on the standard normal distribution assumptions and provide accurate estimations of probabilities within this particular context. Ensure that the Z-value provided corresponds to the standard normal distribution for reliable results.