Calculate the Weibull distribution.

`=WEIBULL.DIST(x,a,b)`

- x - required
- alpha - required
- beta - required
- cumulative - required

`=WEIBULL.DIST(A2,A3,A4,TRUE)`

Using the WEIBULL.DIST function, you can calculate the Weibull cumulative distribution function for a set of terms. This example calculates the Weibull cumulative distribution function for the terms in column A, column B, and column C.

`=WEIBULL.DIST(A2,A3,A4,FALSE)`

You can also calculate the Weibull probability density function for a set of terms using the WEIBULL.DIST function. This example calculates the Weibull probability density function for the terms in column A, column B, and column C.

The WEIBULL.DIST function calculates the Weibull distribution, which is commonly used in reliability analysis.

- The
**WEIBULL.DIST**function is used in reliability analysis to calculate the Weibull distribution. - The function requires three arguments: the value to evaluate, and two parameters to the distribution.

The WEIBULL.DIST function is a statistical function that returns the Weibull distribution. The Weibull distribution is used in reliability analysis.

The parameters of the WEIBULL.DIST function are the x-value, which is the value at which the distribution is to be evaluated, the shape parameter, which is the shape of the distribution, the scale parameter, which is the scale of the distribution, and the cumulative flag, which determines whether the cumulative probability is returned or not.

The shape parameter is a value that determines the shape of the Weibull distribution. It controls how quickly the data converges to the mean.

The scale parameter is a value that determines the scale of the Weibull distribution. It affects the overall spread of the data.

The cumulative flag is a boolean value that determines whether the cumulative probability is returned or not. If the cumulative flag is set to TRUE, the cumulative probability is returned. If the cumulative flag is set to FALSE, the probability density is returned.

Reliability analysis is a statistical method used to estimate the probability of a system or component failing. It uses data on the system's performance over time to make predictions about future performance.

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