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
can be a tricky thing. Consider trying to predict the number rolled
by 2 six-sided dice. We know that 7 is the most likely outcome. We
know the exact probability each number has of being rolled. If we
rolled the dice 100 times, we could calculate the expected value
for the number of times each value would be rolled. However, even
with all that information, we can't definitively predict... 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
People can make mistakes when they test a hypothesis with
statistical analysis. Specifically, they can make either Type I or
Type II errors.
As you analyze your own data and test hypotheses, understanding
the difference between Type I and Type II errors is extremely
important, because there's a risk of making each type of error in
every analysis, and the amount of risk is in your
if... Continue Reading
Welcome to the Hypothesis Test Casino! The featured game of the
house is roulette. But this is no ordinary game of
roulette. This is p-value roulette!
Here’s how it works: We have two roulette wheels, the Null wheel
and the Alternative wheel. Each wheel has 20 slots (instead of the
usual 37 or 38). You get to bet on one slot.
What happens if the ball lands in the slot you bet on? Well,
that depends... 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
A recent discussion on the Minitab
Network on LinkedIn pertained to the I-MR chart. In the
course of the conversation, a couple of people referred to it as
"The Swiss Army Knife of control charts," and that's a pretty great
description. You might be able to find more specific tools for
specific applications, but in many cases, the I-MR chart gets the
job done quite adequately.
When you're... Continue Reading
now I’m enjoying my daily dose of morning joe. As the steam rises
off the cup, the dark rich liquid triggers a powerful enzyme
cascade that jump-starts my brain and central nervous system,
delivering potent glints of perspicacity into the dark crevices of
my still-dormant consciousness.
Feels good, yeah! But is it good for me? Let’s see what the
Drinking more than 4 cups of coffee... Continue Reading
Statistics can be challenging, especially if you're not
analyzing data and interpreting the results every day. Statistical
software makes things easier by handling the arduous
mathematical work involved in statistics. But ultimately, we're
responsible for correctly interpreting and communicating what the
results of our analyses show.
The p-value is probably the most frequently cited
statistic. We... Continue Reading
As a person who loves baking (and eating) cakes, I find it
bothersome to go through all the effort of baking a cake when the
end result is too dry for my taste. For that reason, I decided to
use a designed experiment in Minitab to help me reduce the moisture
loss in baked chocolate cakes, and find the optimal settings of my
input factors to produce a moist baked chocolate cake. I’ll share
the... 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
Histograms are one of the
most common graphs used to display numeric data. Anyone who
takes a statistics course is likely to learn about the histogram,
and for good reason: histograms are easy to understand and can
instantly tell you a lot about your data.
Here are three of the most important things you can learn by
looking at a histogram.
Shape—Mirror, Mirror, On the Wall…
If the left side of a... Continue Reading
by Matthew Barsalou, guest
The old saying “if it walks like a duck, quacks like a duck and
looks like a duck, then it must be a duck” may be appropriate in
bird watching; however, the same idea can’t be applied when
observing a statistical distribution. The dedicated ornithologist
is often armed with binoculars and a field guide to the local birds
and this should be sufficient. A... Continue Reading
Have you ever wanted to know the odds of something happening, or
It's the kind of question that students are frequently asked to
calculate by hand in introductory statistics classes, and going
through that exercise is a good way to become familiar with the
mathematical formulas the underlie probability (and hence, all of
But let's be honest: when class is over, most... Continue Reading
Genichi Taguchi is famous for his pioneering methods of robust
quality engineering. One of the major contributions that he made to
quality improvement methods is Taguchi designs.
Designed experiments were first used by agronomists during
the last century. This method seemed highly theoretical at first,
and was initially restricted to agronomy. Taguchi made the designed
experiment approach more... 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
Have you ever wished your control charts were better? More
effective and user-friendly? Easier to understand and act
on? In this post, I'll share some simple ways to make SPC
monitoring more effective in Minitab.
Common Problems with SPC Control Charts
worked for several years in a large manufacturing plant in which
control charts played a very important role. Virtually thousands of
SPC... Continue Reading
Minitab is the leading provider of software and services for quality
improvement and statistics education. More than 90% of Fortune 100 companies
use Minitab Statistical Software, our flagship product, and more students
worldwide have used Minitab to learn statistics than any other package.
Minitab Inc. is a privately owned company headquartered in State College,
Pennsylvania, with subsidiaries in the United Kingdom, France, and
Australia. Our global network of representatives serves more than 40
countries around the world.