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| Probability Density Function | The formula for the probability density function of the general Weibull distribution is![]() where is the shape parameter, is the location parameter and is thescale parameter. The case where = 0 and = 1 is called the standard Weibull distribution. The case where = 0 is called the 2-parameter Weibull distribution. The equation for the standard Weibull distribution reduces to![]() Since the general form of probability functions can be expressed in terms of the standard distribution, all subsequent formulas in this section are given for the standard form of the function. The following is the plot of the Weibull probability density function. ![]() | ||||||||||||
| Cumulative Distribution Function | The formula for the cumulative distribution function of the Weibull distribution is![]() The following is the plot of the Weibull cumulative distribution function with the same values of as the pdf plots above.![]() | ||||||||||||
| Percent Point Function | The formula for the percent point function of the Weibull distribution is![]() The following is the plot of the Weibull percent point function with the same values of as the pdf plots above.![]() | ||||||||||||
| Hazard Function | The formula for the hazard function of the Weibull distribution is![]() The following is the plot of the Weibull hazard function with the same values of as the pdf plots above.![]() | ||||||||||||
| Cumulative Hazard Function | The formula for the cumulative hazard function of the Weibull distribution is![]() The following is the plot of the Weibull cumulative hazard function with the same values of as the pdf plots above.![]() | ||||||||||||
| Survival Function | The formula for the survival function of the Weibull distribution is![]() The following is the plot of the Weibull survival function with the same values of as the pdf plots above.![]() | ||||||||||||
| Inverse Survival Function | The formula for the inverse survival function of the Weibull distribution is![]() The following is the plot of the Weibull inverse survival function with the same values of as the pdf plots above.![]() | ||||||||||||
| Common Statistics | The formulas below are with the location parameter equal to zero and the scale parameter equal to one.
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| Parameter Estimation | Maximum likelihood estimation for the Weibull distribution is discussed in theReliability chapter (Chapter 8). It is also discussed in Chapter 21 of Johnson, Kotz, and Balakrishnan. | ||||||||||||
| Comments | The Weibull distribution is used extensively in reliability applications to model failure times. | ||||||||||||
| Software | Most general purpose statistical software programs support at least some of the probability functions for the Weibull distribution. | ||||||||||||
Gertrude Cox : Gertrude Mary Cox (of Experimental Statistics at North Carolina State University. She was later appointed director of both the Institute of Statistics of 1900 - 1978) was an influential American statistician and founder of the department the Consolidated University of North Carolina and the Statistics Research Division of North Carolina State University. Her most important and influential research dealt with experimental design; she wrote an important book on the subject with W. G. Cochran. In 1949 Cox became the first female elected into the International Statistical Institute and in 1956 she was president of the American Statistical Association. From 1931 to 1933 Cox undertook graduate studies in statistics at the University of California at Berkeley , then returned to Iowa State College as assistant in the Statistical Laboratory. Here she worked on the design of experiments . In 1939 she was appointed assistant professor of statisti...

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is the gamma function![GAMMA(a) = INTEGRAL[t**(a-1)*EXP(-t)dt] where the
integration is from 0 to infinity](http://www.itl.nist.gov/div898/handbook/eda/section3/eqns/gammfunc.gif)



![SQRT[GAMMA((gamma+2)/gamma) - (GAMMA((gamma+1)/gamma))**2]](http://www.itl.nist.gov/div898/handbook/eda/section3/eqns/weisd.gif)

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