Intro to Basic QA Statistics Series (Part 1)

REFLECTION: FOR STUDENTS: Don’t throw your stat’s books away. You will use them one day, and unlike most other textbooks, old statistics textbooks are usually just as valid as they were years ago.

FOR ACADEMICS: Yes, teach your students to use R and Minitab, but be sure they can do the calculations by hand

FOR PROFESSIONALS/PRACTITIONERS: I know you likely are old hands at this, but thank you for any advice you can provide those entering the QA field who have questions. Stats sometimes seems mystifying, so be sure to share the knowledge with mentorship.

Foundation

Most in the industrial world understand that tracking and analysis of data is a requirement to know if a process is producing waste or if your process is stable and everything is running as it should. The problem that arises from time to time is the “craftsman attitude” of a process owner, or perhaps even that same attitude in a plant manager.
What I am describing with the term -“craftsman attitude”- is the acquired belief of a knowledgeable Subject Matter Expert or Expert Operator, which leads a person to decide of their own accord they are wise enough to make a critical decision without proper Data Analysis.

At this point in any conversation with a person trying to argue they do not need Data, I would quote Deming- “In God we trust, all others must bring DATA.”

This phenomenon is likely a combination of two primary things:
Resistance to Change and a natural aversion (at least in Western Society) to developing a deep understanding of mathematics. Resistance to Change is inherent in many human beings and very hard to overcome. Awareness of the potential Resistance and how it may influence your decisions can help mitigate how you react to Quality Improvement issues.

Mathematics is something you must pursue on your own unless you were gifted with a natural aptitude (as the school systems are not very effective when it comes to producing mathematically educated high school graduates). Fear not.
Lack of mathematical prowess means very little in this day and age. You need only understand the basic concepts of statistics and how to apply them, and most stats software will walk you through the rest.

This post will be the first of a few on basic stats to help those who may feel like it is beyond them to help show that it is not that complicated.
I will be keeping the stats on a basic level, and breaking the posts up into digestible bits, so please continue reading 😊

Basic Statistical Terms

The first terms that should be understood first are Population, Sample, Statistic, and Parameter.

-A Population considers every member/unit of a group
-A Sample would be a random surveillance study of a portion of the Population
-A Parameter is Derived from Analysis of the Population
-A Statistic is Derived from Analysis of the Sample of the Population

Conclusion

A Parameter is a description of an entire group (Population). A Statistic is the description of a sample of the Population. Understanding the difference is critical. A Parameter indicates that the whole population has been evaluated in some way to obtain the result.
A Statistic depends upon randomness and sample size to adequately estimate the outcome of the population parameter.
The larger the random sample, the better!
If you have the time and resources, always choose a larger sample size!
-Next Time: Basic Measures of Central Tendency

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