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
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
T'was the season for toys recently, and Christmas day found me
playing around with a classic, the Etch-a-Sketch. As I noodled with
the knobs, I had a sudden flash of recognition: my drawing reminded
me of the Empirical CDF Plot in Minitab Statistical Software. Did you just ask,
"What's a CDF plot? And what's so empirical about it?" Both very
good questions. Let's start with the first, and we'll... Continue Reading
In my last post on
DMAIC tools for the Define phase, we reviewed various graphs
and stats typically used to define project goals and
customer deliverables. Let’s now move along to the tools you can
use in Minitab
Statistical Software to conduct the Measure phase.
Measure Phase Methodology
The goal of this phase is to measure the process to
determine its current performance and quantify the problem.... Continue Reading
you’re working in Minitab and prepping your data for analysis, it’s
common to group data into categories that imply a specific order,
such as Low, Medium, High or Beginning, Middle, End.
But if the data were to appear in a different order in tables
and graphs (for example, Beginning, End, Middle), the result could
be confusing, and might distract from your message.
Fortunately, with Minitab’s va...Continue Reading
we enter late December, snow is falling here on the East Coast of
the United States. The official start to winter is on December 21,
2016, but it’s certainly not uncommon to see snowflakes flying
before this date.
If you live in the U.S., you know the winter of 2015 was one for
the record books. In fact, more than 90 inches of snow fell in
Boston in the winter of 2015! Have you ever wondered how... Continue Reading
If you’re familiar with Lean Six Sigma, then you’re familiar
DMAIC is the acronym for Define, Measure, Analyze, Improve and
Control. This proven problem-solving strategy provides a structured
5-phase framework to follow when working on an improvement
This is the first post in a five-part series that focuses on the
tools available in Minitab Statistical
Software that are most... Continue Reading
2016 comes to a close, it’s time to reflect on the passage of time
and changes. As I’m sure you’ve guessed, I love statistics and
analyzing data! I also love talking and writing about it. In fact,
I’ve been writing statistical blog posts for over five years, and
it’s been an absolute blast. John Tukey, the renowned statistician,
once said, “The best thing about being a statistician... Continue Reading
In Part 1 of this
blog series, I wrote about how statistical inference uses data
from a sample of individuals to reach conclusions about the whole
population. That’s a very powerful tool, but you must check your
assumptions when you make statistical inferences. Violating any of
these assumptions can result in false positives or false negatives,
thus invalidating your results.
The common data... Continue Reading
Statistical inference uses data from a sample of individuals to
reach conclusions about the whole population. It’s a very
powerful tool. But as the saying goes, “With great
power comes great responsibility!” When attempting to make
inferences from sample data, you must check your assumptions.
Violating any of these assumptions can result in false positives or
false negatives, thus invalidating... Continue Reading
Since the release of Minitab
Express in 2014, we’ve often received questions in technical
support about the differences between Express and Minitab 17.
In this post, I’ll attempt to provide a comparison between these
two Minitab products.
What Is Minitab 17?
Minitab 17 is an all-in-one graphical and statistical analysis
package that includes basic analysis tools such as hypothesis
testing,... Continue Reading
The ultimate goal of most quality improvement projects is clear:
reducing the number of defects, improving a response, or making a
change that benefits your customers.
We often want to jump right in and start gathering and analyzing
data so we can solve the problems. Checking your measurement
systems first, with methods like attribute agreement analysis or
Gage R&R, may seem like a needless waste... Continue Reading
We’ve got a plethora of case studies showing how businesses from different
industries solve problems and implement solutions with data
analysis. Take a look for ideas about how you can use data analysis
to ensure excellence at your business!
Boston Scientific, one of the world’s leading developers of
medical devices, is just one organization who has shared their
story. A team at their Heredia,... Continue Reading
mining uses algorithms to explore correlations in data sets. An
automated procedure sorts through large numbers of variables and
includes them in the model based on statistical significance alone.
No thought is given to whether the variables and the signs and
magnitudes of their coefficients make theoretical sense.
We tend to think of data mining in the context of big data, with
its huge... Continue Reading
In regression, "sums of squares" are used to represent
variation. In this post, we’ll use some sample data to walk through
sample data used in this post is available within Minitab by
choosing Help > Sample Data,
or File > Open Worksheet >
Look in Minitab Sample Data folder (depending on
your version of Minitab). The dataset is called
ResearcherSalary.MTW, and contains data... Continue Reading
See if this
sounds fair to you. I flip a coin.
Heads: You win
$1.Tails: You pay me $1.
You may not like games of chance, but you have to admit it seems
like a fair game. At least, assuming the coin is a normal, balanced
coin, and assuming I’m not a sleight-of-hand magician who can
control the coin.
How about this next
You pay me $2 to play.I flip a coin over and over until
it comes up heads.Your... Continue Reading
Figures lie, so they say, and liars figure. A recent post at Ben
Orlin's always-amusing mathwithbaddrawings.com blog nicely
encapsulates why so many people feel wary about anything
related to statistics and data analysis. Do take a moment to check it out, it's a fast
all of the scenarios Orlin offers in his post, the statistical
statements are completely accurate, but the person offering... Continue Reading
Often, when we start analyzing
new data, one of the very first things we look at is whether
certain pairs of variables are correlated. Correlation can tell if two variables have a
linear relationship, and the strength of that
makes sense as a starting point, since we're usually looking for
relationships and correlation is an easy way to get a quick handle
on the data set we're... Continue Reading
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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.
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