GAMMA.INV
The GAMMA.INV function calculates the inverse of the gamma cumulative distribution function (CDF) for a specified probability.
Syntax 🔗
=GAMMA.INV(Probability, Alpha, Beta)
Probability | The probability for which you want to find the inverse gamma distribution. |
Alpha | The shape parameter of the gamma distribution. |
Beta | The scale parameter of the gamma distribution. |
About GAMMA.INV 🔗
GAMMA.INV is a handy Excel function for working with gamma distribution probabilities. It operates by providing you with the inverse probability value for a gamma distribution given the shape parameter (alpha) and the scale parameter (beta). This function is particularly useful in statistical analysis and modeling where gamma distributions are commonly used to represent positive continuous variables with skewed distributions. By utilizing GAMMA.INV, you can efficiently determine the input value that corresponds to a specified cumulative probability in gamma distribution scenarios.
Examples 🔗
If you have a gamma distribution with alpha = 2 and beta = 3, and you want to find the input value that corresponds to a cumulative probability of 0.8, you can use the formula: =GAMMA.INV(0.8, 2, 3). This will give you the input value for the specified probability in the gamma distribution.
Suppose you are analyzing a dataset with gamma-distributed variables and you need to find the value that represents the 90th percentile of the distribution with alpha = 1.5 and beta = 2. You would use: =GAMMA.INV(0.9, 1.5, 2). This formula will return the value at the 90th percentile of the specified gamma distribution.
Notes 🔗
Ensure that the provided probability falls within the valid range for the gamma distribution. The GAMMA.INV function assumes that the provided parameters (alpha and beta) are numerical values representing the shape and scale of the gamma distribution. It also operates under the assumption that the gamma distribution is well-defined for the given input parameters.
Questions 🔗
You should use the GAMMA.INV function when you need to find the inverse of the gamma cumulative distribution function for specific probabilities in datasets with gamma-distributed variables. It helps in determining the input values corresponding to desired cumulative probabilities on gamma distributions.
What do the shape and scale parameters signify in the GAMMA.INV function?In the GAMMA.INV function, the shape parameter (Alpha) defines the skewness and shape of the gamma distribution curve, while the scale parameter (Beta) influences the scale or spread of the distribution.
No, the GAMMA.INV function expects probabilities within the valid range of 0 to 1. Inputting probabilities outside this range may result in errors or unexpected outputs.