If you’re improving a process and you suspect your current settings are not near the optimum, the method of steepest ascent is one of the fastest, most practical tools in response surface methodology (RSM). It uses a first-order model (a local linear approximation) to compute the direction of maximum increase—then applies sequential experimentation by running […]
Using the Range to Estimate Variability (d₂, d₂*): A Guide to t, F, CIPractical Guide to t-tests, F-tests, and Confidence Intervals
Using the Range to Estimate Variability (d₂, d₂*): A Practical Guide to t-tests, F-tests, and Confidence Intervals Abstract This article explains how the statistical range can be applied as a practical estimator of process spread in quality engineering and research. By using the range to estimate variability, practitioners can approximate the population standard deviation efficiently […]
Runs Test for Detecting Non-Randomness using Excel in 10 Steps [GUIDE]Learn how to detect sustained special cause shifts in the process mean
Runs Test for Detecting Non-Randomness using Excel The goal of any continuous improvement program is having a process that exhibits a state of statistical control. So, having a way to detect when a process is going out of statistical control is an important feature of a monitoring system. A system that exhibits statistical control yields […]
12 Steps to Testing for Normality using Excel 2016 [GUIDE]Learn how to Test for Normality using the Anderson Darling Statistical Procedure
Testing for normality using Excel is a routine procedure for Quality Engineers. In this post, I’ll show you how to test for normality using the Anderson Darling procedure. Using this procedure we will learn how to compute the Anderson Darling test statistic and p-value for a normal distribution. We will also compute an Anderson Darling […]
Estimating the d2 constant and the d3 constant using Minitab
In this video tutorial I show how you can estimate the d2 constant and d3 constant. Employing Minitab, we will generate k = 1 million subgroups where each subgroup has n=2 values. Using this simulated data, we will estimate the control chart constants; d2 and d3. For this case, the real value of the d2 […]