Let's find the motivation to use reliability statistics and find the resources to learn the statistical tools necessary to succeed.

This chapter introduces the lognormal distribution, emphasizing its asymmetrical probability density curve compared to traditional bell curves. It discusses the implications of skewness for central tendency measures and how the nature of failure modeling impacts the choice between lognormal and normal distributions. Through examining characteristics like cumulative distribution functions and hazard rates, the chapter highlights the practical complexities and limitations of using lognormal distributions in reliability engineering.
Some of you might have heard of the bell curve.' Some of you might have heard that the bell curve' is sometimes called the normal distribution.' There is a reason it is called normal but that is not always obvious. But then there is the lognormal distribution.' What is this? and how does it relate back to the bell curve?' There is a really good reason for this link. And the good thing is that all you need is just a little bit of knowledge about how something breaks (and is repaired) to help use the lognormal distribution to help you make lots of important decisions easily!
This Accendo Reliability webinar was originally broadcast on 28 January 2025.
To view the recorded video/audio and PDF workbook of the event, visit the webinar page.
Lognormal Distribution, Concepts and Applications article/video
Lognormal Distribution article
Calculating Lognormal Distribution Parameters article<
Results-Driven Decisions, Faster: Accelerated Stress Testing as a Reliability Life Test episode
When it's Not Normal: How to Choose from a Library of Distributions episode
Let's find the motivation to use reliability statistics and find the resources to learn the statistical tools necessary to succeed.
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