A factorial experiment is the simultaneous manipulation of factors at different levels to see their effect on some desired result. A factorial experiment could be ‘a full factorial’ or it could be a ‘fractional factorial’ experiment. If the experiment is fractionated, the practitioner gives up something in the sense that main effects are aliased with interactions, or interactions are aliased with other interactions, and so forth. A full fractional factorial experiment has none of the aliasing, but it cost more because you have to run more experimental trials.

The F-distribution is another distribution that is used extensively in statistical analysis to test certain hypotheses arising from the comparison of two or more normal distributions. One of the ‘operational definitions’ of quality follows: Quality is considered the minimum deviation around a target value. We often spend a significant amount of time and money making sure our processes are ‘targeted’ appropriately, but it is just as important to assure that processes are operating as consistently (that is, with as little variation) as possible.

A flowchart (also known as a process flow diagram) is a graphical tool that depicts distinct steps of a process in sequential order (from top to bottom of the page). The basic idea is to include all of the steps of critical importance to the process. Also, flowcharts are often annotated with performance information.

Kanban is a Japanese term that literally means ‘sign-board.’ Kanban is a scheduling system for lean and Just-In-Time (JIT) production. According to its creator, Taiichi Ohno, kanban (a signal to produce) is a means through which JIT is achieved.

An interrelationship diagram shows graphically the cause-effect relationships that exist among a group of items, issues, problems, or opportunities. It is particularly useful in helping to identify the potential causal relationships that might lie behind a problem that continues to reoccur despite attempts to resolve it.

The alternate hypothesis is the complement of the null hypothesis. The null hypothesis is what you anticipate through randomness. The alternative hypothesis, sometimes known as the alternate hypothesis is the opposite of that. It is what you would not anticipate by randomness. More often than not you are trying to reject the null because you are trying to see a change in something – considering that most six sigma projects are trying to fix broken processes.

A hypothesis test is a method for making rational decisions about the reality of effects. Most decisions require choosing from one or more alternatives. The decision is based on incomplete information. A team might be considering using a different method which they believe will give them a better result. Their theory is that method A is going to be better than method B.

Let’s start off by talking about descriptive statistics. Descriptive statistics describe data collected. Measures of central tendency, such as mean and median, and measures of dispersion such as standard deviation and range, are used to summarize and interpret some of the properties of a data set (e.g., sample, or subgroup) are known as descriptive statistics. Descriptive statistics can actually be verified from the data provided. Example: Of the citations for speeding issued in July by Officer Hunt, 23% were given to drivers of red cars. This can be verified by looking at Officer Hunt’s July citation record.

A mathematical method that employs probability theory for inferring the properties of a population parameter from which the sample is taken is known as inferential statistics. Inferential statistics is a set of methods used to make generalizations, estimations, or predictions. Let’s say that we want to determine the statistical capability of a process. And, let’s say that 28 machines are producing a particular part. This process has 14 operators that run the parts. The operators use their own micrometers to measure key characteristics of the parts. There are three sources of raw materials that feed into the process. The process runs two shifts per day five days a week.

Dr. Genichi Taguchi, a Japanese quality consultant and engineer, came to the United States in the 1980s concentrates on loss. In conjunction with this view of quality, he developed the idea of a loss function. If we think of quality in a competitive way, we should view that there is a target value (i.e., nominal-is-best, larger-is-best, or smaller-is-best). When measuring an end-product-parameter, any departure away from the designer’s intended target creates a loss to society, or a loss to the producer. Either way, ultimately the customer ends up paying for it.