In the previous post I showed how to solve a simple problem by performing an Analysis of Variance (if you haven’t read it, please click here). The example was about three different methods to perform a task and we wanted to know if we are getting different results or the variations on the data are only due to the population dispersion.
Generally speaking, we compared the variances between the three samples and the variances within each sample and used the Variance Ratio Test to know, with a specific confidence interval, if the samples are coming from the same population, which in practical terms (referred to our example) means that the different methods are not changing the outcomes. In our example we rejected this hypothesis, so we can say that there is a significant difference between the methods. Continue reading →
In manufacturing environments, as well as in many other settings, we take actions and modify parameters, procedures and processes to obtain a specific result (usually to improve the situation). In these cases we need to know if the obtained result is a expected consequence of our changes or we’re just observing variations inherent to the population, that are not related to our actions.
One of the techniques we can use is the Analysis of Variance which is a powerful tool used in statistical design of experiments, Lean Manufacturing, Reliability Engineering and in situations involving many variables and/or samples from different populations.
It’s true that many software can perform this calculation automatically; however, it’s important to know how the method works – at least with a simple example like the one below – to be able to interpret and take advantage of the results the software we’ll give us when solving more complex problems. Continue reading →