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

You may fondly, or most likely not fondly, remember your undergraduate course on probability and statistics. The calculations of various winning hands with card games were interesting and connected to the early invention' of probability and statistical methods. Yet, the jar with colored beads was rather boring.
From drive time to upload speeds, from production output per hour to defects per unit, we are surrounded by things and processes that vary. With most things, there are many factors at play contributing to variation. Those variations and the means to discuss them in a meaningful way are the essence of statistics.
Let's explore the many ways we use, or should use, statistics in our engineering role. From gathering data to presenting, from analyzing to comparing, we have a wide range of tools available that probably' (pun intended) will have a significant' (did it again) impact on your ability to make a difference with what you do.
This Accendo Reliability webinar was originally broadcast on 8 February 2022.
The Fundamental Thing to Know from Statistics for Design Engineering episode
Reliability and Statistics episode
Statistics for Reliability Engineers episode
Statistics, Mechanisms, Facilitation episode
Practical Way to Learn Statistics episode
Let's find the motivation to use reliability statistics and find the resources to learn the statistical tools necessary to succeed.
Let's explore R software's many capabilities concerning reliability statistics from field data analysis, to statistical process control.
Let's explore an array of distributions and the problems they can help solve in our day-to-day relaibility engineering work.
Perry discusses the basics of DOE (design of experiments) and fundamentals so you can get started with they useful product development tool.
Let's discuss the 6 basic considerations to estimate the necessary sample size to support decision making.
When we make a measurement, we inform a decision. It's important to have data that is true to the actual value.
One of the first things I learned about data analysis was to create a plot, another, and another. Let the data show you what needs attention.
If you want a really easy introduction or review of these functions that help inform a decision then check out this webinar.
Sometimes we have to work out how many of them we need (if they make up a fleet) or how many spare parts we need to keep them running.
Let's explore the ways we use, or should use, statistics as engineers. From gathering data to presenting, from analyzing to comparing.
Let's explore what residuals are, where they come from, and how to evaluate them to detect if the fitted line (model) is adequate or not.
This webinar is a light (re)introduction into common mathematical symbols used in many engineering scenarios including reliability.
Reliability is a measure of your product or system. Confidence is a measure of you. But we often forget this.
How to calculate Gage discrimination - the more useful result for a design situation, and even how to use it for destructive tests.
For those who conduct reliability data analysis or turning a jumble of dots (data points) into meaningful information
It is not just a pretty shape' that seems to work, It comes from a really cool physical phenomena that we find everywhere.
Let's examine a handful of parametric and non-parametric comparison tools, including various hypothesis tests.
You need to have a good idea of the probability distribution of the TTF of your product when it comes to reliability engineering.
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