Your Reliability Engineering Professional Development Site
The basis of DOE analysis is comparing two samples. This methodology can be used just as well for changing one variable or more than one variable as in DOEs. Comparison of means is as simple as the t-test.
Some people initially feel intimidated considering the connection of DOE with statistics. Once they understand it in simple terms, the topic comes together for them.
So let’s see if we can accomplish that for you now. [Read more…]
In another post, I started the discussion about variability and interquartile range. This is part 2 of that discussion and will focus on variance.
With rare exception, most distributions or groups of data require more than one parameter (or statistic) to fully describe both the location and spread (scale and shape) of the group of data. Is the data clumped tightly about some value, or spread out over a wide range. [Read more…]
There are rare situations when we would like to estimate the reliability at the lower confidence level after estimating the mean from a sample (often a test result). And, to make even more rare of a situation, we know the population standard deviation. [Read more…]
Ideally, in every design of every component, the stress – strength relationship looks like this figure. The stress is well below the strength. [Read more…]
In the analysis of repairable equipment, one may need to make the assumption of constant failure rate. In my opinion, anytime one wants to make the assumption of constant failure rate, it should be validated. [Read more…]
An error that I see on occasion is the use of statistical confidence with a goal or target value. For example, we want 95% reliability at five years with 90% confidence. What does that mean? [Read more…]
Let’s work a sample size problem.
A random sample size, n, is to be taken from a large population having a standard deviation of 1″. The sample size is to be determined so that there well be a 0.05 risk probability of exceeding a 0.1″ tolerance error in using the sample mean to estimate μ. Which of the following values is nearest the required sample size?
a. 42
b. 106
c. 203
d. 384 [Read more…]
I recently received a question concerning what sample size to use when assessing call center calls. Not a lot of information in the request, so my answer was rather general. And, thought it might provide some insight to others facing sample size questions of their own. [Read more…]
The lognormal distribution has two parameters, μ, and σ. These are not the same as mean and standard deviation, which is the subject of another post, yet they do describe the distribution, including the reliability function. [Read more…]