Easy access to the right tools makes any task easier. That
simple idea has made the Swiss Army knife essential for
adventurers: just one item in your pocket gives you instant access
to dozens of tools when you need them.
your current adventures include analyzing data, the multifaceted
Editor menu in Minitab Statistical
Software is just as essential.
Minitab’s Dynamic Editor Menu
Whether you’re... Continue Reading
It's a very exciting time at Minitab's offices around the world
because we've just announced the availability of
Minitab® 18 Statistical Software.
is everywhere today, but to use it to make sound, strategic
business decisions, you need to have tools that turn that data into
knowledge and insights. We've designed Minitab 18 to do
We've incorporated a lot of new
features, made some... Continue Reading
Before cutting an expensive piece of granite for a countertop, a
good carpenter will first confirm he has measured correctly. Acting
on faulty measurements could be costly.
no measurement system is perfect, we rely on such systems to
quantify data that help us control quality and monitor changes in
critical processes. So, how do you know whether the changes you see
are valid and not just the... Continue Reading
Users often contact Minitab technical support to ask how the
software calculates the control limits on control charts.
A frequently asked question is how the control limits are
calculated on an
I-MR Chart or Individuals Chart. If Minitab plots the upper and
lower control limits (UCL and LCL) three standard deviations above
and below the mean, why are the limits plotted at values other than
3 times... Continue Reading
"Data! Data! Data! I can't make bricks without clay."
— Sherlock Holmes, in Arthur Conan Doyle's The Adventure
of the Copper Beeches
Whether you're the world's greatest detective trying to crack a
case or a person trying to solve a problem at work, you're going to
need information. Facts. Data, as Sherlock Holmes
But not all data is created equal, especially if you plan to
analyze as part of... Continue Reading
Choosing the right type of subgroup in a control chart is
crucial. In a rational subgroup, the variability within a subgroup
should encompass common causes, random, short-term variability and
represent “normal,” “typical,” natural process variations, whereas
differences between subgroups are useful to detect drifts in
variability over time (due to “special” or “assignable” causes).
Variation within... Continue Reading
Earlier, I wrote about the
different types of data statisticians typically encounter. In
this post, we're going to look at why, when given a choice in the
matter, we prefer to analyze continuous data rather than
categorical/attribute or discrete data.
As a reminder, when we assign something to a group or give it a
name, we have created attribute or
categorical data. If we count something,
like... Continue Reading
You run a capability analysis
and your Cpk is bad. Now what?
First, let’s start by defining
what “bad” is. In simple terms, the smaller the Cpk, the more
defects you have. So the larger your Cpk is, the
practitioners use a Cpk of 1.33 as the gold standard, so we’ll
treat that as the gold standard here, too.
Suppose we collect some data and run a capability analysis using
In Part 1 of Gauging Gage, I looked at how adequate a
sampling of 10 parts is for a Gage R&R Study and providing
some advice based on the results.
Now I want to turn my attention to the other two factors in the
standard Gage experiment: 3 operators and 2 replicates.
Specifically, what if instead of increasing the number of parts in
the experiment (my previous post demonstrated you would need... Continue Reading
"You take 10 parts and have 3 operators measure each 2
This standard approach to a Gage R&R experiment is so
common, so accepted, so ubiquitous that few people ever question
whether it is effective. Obviously one could look at whether
3 is an adequate number of operators or 2 an adequate number of
replicates, but in this first of a series of posts about
"Gauging Gage," I want to look at... Continue Reading
Everyone who analyzes data regularly has the experience of
getting a worksheet that just isn't ready to use. Previously I
wrote about tools you can use to
clean up and eliminate clutter in your data and
reorganize your data.
In this post, I'm going to
highlight tools that help you get the most out of messy data by
altering its characteristics.
Know Your Options
Many problems with data don't become... Continue Reading
You've collected a bunch of
data. It wasn't easy, but you did it. Yep, there it is, right
there...just look at all those numbers, right there in neat columns
and rows. Congratulations.
I hate to ask...but what are you
going to do with your data?
If you're not sure precisely
what to do with the data you've got, graphing it is a
great way to get some valuable insight and direction. And a good
graph to... Continue Reading
In my last post, I wrote about
making a cluttered data set easier to work with by removing
unneeded columns entirely, and by displaying just those columns you
want to work with now. But
too much unneeded data isn't always the problem.
What can you do when someone
gives you data that isn't organized the way you need it to be?
That happens for a variety of
reasons, but most often it's because the... Continue Reading
Isn't it great when you get a set of data and it's perfectly
organized and ready for you to analyze? I love it when the people
who collect the data take special care to make sure to format it
consistently, arrange it correctly, and eliminate the junk,
clutter, and useless information I don't need.
never received a data set in such perfect condition, you say?
Yeah, me neither. But I can... Continue Reading
In its industry guidance to companies that manufacture drugs and
biological products for people and animals,
the Food and Drug Administration (FDA) recommends three stages for
Process Qualification, and Continued Process Verification. In
this post, we we will focus on that third stage.
Stage 3: Continued Process Verification
Per the FDA guidelines, the goal of... Continue Reading
many, my introduction to 17th-century French philosophy came at the
tender age of 3+. For that is when I discovered the
Etch-a-Sketch®, an entertaining ode to Descartes' coordinate plane.
Little did I know that the seemingly idle hours I spent doodling
on my Etch-a-Sketch would prove to be excellent training for the
feat that I attempt today: plotting an Empirical Cumulative
Distribution... Continue Reading
To make objective
decisions about the processes that are critical to your
organization, you often need to examine categorical data. You may
know how to use a t-test or ANOVA when you’re comparing measurement
data (like weight, length, revenue, and so on), but do you know how to compare
attribute or counts data? It easy to do with statistical software
One person may look at
this bar... Continue Reading
by Rehman Khan, guest blogger
There are many articles giving
Minitab tips already, so to be different I have done
mine in the style of my books, which use example-based learning. All
ten tips are shown using a single example.
If you don’t already know these 10 tips you will get much more
benefit if you work along with the example. You don’t need to
download any files to work along—although, if you... Continue Reading
In its industry guidance to companies that manufacture drugs and
biological products for people and animals, the Food and Drug
Administration (FDA) recommends three stages for process
my last post covered
statistical tools for the Process Design stage, here we will
focus on the statistical techniques typically utilized for the
second stage, Process Qualification.
Stage 2: Process... Continue Reading
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