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This is my second video on Sample Size in Reliability Testing! In this video, we will explain the Weibayes Approach to estimate sample size and estimating test length when sample size and shape parameter is known.
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Dear friends, I am happy to release this video about determining sample size in reliability and functional testing! The video discusses determining sample size with Success Run Theorem (or Success Testing) will zero failures as well as given number of failures. I have illustrated use of basic formula and calculation as well as use of various templates to determine sample size. Hope you find this important and interesting!
This is part-1 of my videos on sample size! We recommend viewers to watch our video on Binomial Distribution before watching this video, in case they have not seen it before
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Anybody who did some hardware test in they life, eventually will face the question of sample size.
Probably it will be a tradeoff between the test duration and amount of samples to test.
So how much is enough? One, three, ten?
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The planning of environmental or reliability testing becomes a question of sample size at some point.
It’s probably the most common question I hear as a reliability engineer – how many samples do we need. [Read more…]
The operating characteristic curve, OC curve, visualizes a sampling plan.
At times, we select a sample from a group of items and evaluate them. Does this lot of widgets meet the specifications? Does this batch measure up? [Read more…]
Detecting a change or difference is often the aim of an experiment or set of measurements. We want to learn which vendor, process, or design provides a better result.
When we use a sample to estimate a statistic for a population we take the risk that the sample provides values that are not representative of the population. For example, if we use a professional basketball team to sample men’s height. We may conclude that the height of men in the general population is taller than the true population value. [Read more…]
Hypothesis testing permits us to compare two groups of items and determine if there is a significant difference or not. There are many types of hypothesis tests depending on the specific question, type of data, and what is or is not known when designing the test. [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…]
Reaching for a goal may include taking some risks. In reliability testing, we are often limited by the number of samples available for testing. And, in the case where time is available or the acceleration factor is high we can take advantage of testing longer. [Read more…]
One of the most often asked questions of reliability professionals (or statisticians) is related to how many samples for a test? This typically is not an easy question to resolve without some work and knowledge of the testing in question. We are often asked anyway, and expected to have an answer.
While not the most often asked question on the CRE exam, you might see something related. Budget planning, prototype counts, test equipment sizing, etc. all need an estimate for sample size. [Read more…]