Earlier this month, PLOS.org
published an article titled "Ten Simple Rules for Effective Statistical
10 rules are good reading for anyone who draws conclusions and makes decisions
based on data, whether
you're trying to extend the boundaries of scientific knowledge or
make good decisions for your business.
Carnegie Mellon University's
Robert E. Kass and several co-authors devised... Continue Reading
outlier is an observation in a data set that lies a substantial
distance from other observations. These unusual observations can
have a disproportionate effect on statistical analysis,
such as the mean, which can lead to misleading results.
Outliers can provide useful information about your data or process,
so it's important to investigate them. Of course, you have to find
Finding... Continue Reading
Businesses are getting more and more data from existing and
potential customers: whenever we click on a web site, for example,
it can be recorded in the vendor's database. And whenever we use
electronic ID cards to access public transportation or other
services, our movements across the city may be analyzed.
In the very near future, connected objects such as cars and
electrical appliances will... Continue Reading
last thing you want to do when you purchase a new piece of software
is spend an excessive amount of time getting up and running. You’ve
probably been ready to the use the software since, well,
yesterday. Minitab has always focused on making our
software easy to use, but many professional software packages do
have a steep learning curve.
Whatever package you’re using, here are three things you... Continue Reading
Suppose you’ve collected data on cycle time, revenue, the
dimension of a manufactured part, or some other metric that’s
important to you, and you want to see what other variables may be
related to it. Now what?
When I graduated from college with my first statistics degree,
my diploma was bona fide proof that I'd endured hours and hours of
classroom lectures on various statistical topics, including
This is an era of massive data. A huge amount of data is being
generated from the web and from customer relations records, not to
mention also from sensors used in the manufacturing industry
(semiconductor, pharmaceutical, petrochemical companies and many
Univariate Control Charts
In the manufacturing industry, critical product characteristics
get routinely collected to ensure... Continue Reading
Do you recall my “putting the cart before the horse” analogy in
part 1 of this blog series? The comparison is simple.
We all, at times, put the cart before the horse in relatively
innocuous ways, such as eating your dessert before you’ve eaten
your dinner, or deciding what to wear before you’ve been invited to
the party. But performing some tasks in the wrong order, such as
running a statistical... Continue Reading
Once upon a time, when people wanted to compare the standard
deviations of two samples, they had two handy tests available, the
F-test and Levene's test.
Statistical lore has it that the F-test is so named because
it so frequently fails you.1
Although the F-test is suitable for data that are normally
distributed, its sensitivity to departures from
normality limits when and where it can be used.
Leve... Continue Reading
Along with the explosion of interest in visualizing data over
the past few years has been an excessive focus on how attractive
the graph is at the expense of how useful it is. Don't get me
wrong...I believe that a colorful, modern graph comes across better
than a black-and-white, pixelated one. Unfortunately, however, all
the talk seems to be about the attractiveness and not the value of
the... Continue Reading
Like so many of us, I try to stay healthy by watching my weight.
I thought it might be interesting to apply some statistical
thinking to the idea of maintaining a healthy weight, and the
central limit theorem could provide some particularly useful
insights. I’ll start by making some simple (maybe even simplistic)
assumptions about calorie intake and expenditure, and see where
those lead. And then... Continue Reading
You have a column of categorical data. Maybe it’s a column of
reasons for production downtime, or customer survey responses, or
all of the reasons airlines give for those riling flight delays.
Whatever type of qualitative data you may have, suppose you want to
find the most common categories. Here are three different ways to
1. Pareto Charts
Pareto Charts easily help you separate the vital...Continue Reading
If you need to assess process
performance relative to some specification limit(s),
capability is the tool to use. You collect some accurate
data from a stable process, enter those measurements in Minitab,
and then choose Stat > Quality Tools >
Capability Analysis/Sixpack or Assistant
> Capability Analysis.
Now, what about sorting the data?
I’ve been asked “why does Cpk change when I... Continue Reading
In my time at Minitab, I’ve gotten a good understanding of what
types of graphs users create. Everyone knows about histograms, bar
charts, and time series plots. Even relatively less familiar plots
like the interval plot and
individual value plot are still used quite often.
However, one of the most underutilized graphs we have available is
the area graph. If you’re not familiar with an Area... Continue Reading
In an earlier post, I shared an
overview of acceptance sampling, a method that lets you
evaluate a sample of items from a larger batch of products (for
instance, electronics components you've sourced from a new
supplier) and use that sample to decide whether or not you should
accept or reject the entire shipment.
There are two approaches to acceptance sampling. If you do it by
attributes, you... Continue Reading
If you're just getting started in the world of quality
improvement, or if you find yourself in a position where you
suddenly need to evaluate the quality of incoming or outgoing
products from your company, you may have encountered the term
"acceptance sampling." It's a statistical method for evaluating the
quality of a large batch of materials from a small sample of items,
In my last post, I walked
through the steps to
install Minitab 17 on a Mac using Apple Boot Camp.
Minitab 17 can also be installed on a Mac using desktop
In addition to your Mac, you’ll need:
A copy of Windows 7 or later version ISO
Minitab 17 Statistical Software
Desktop virtualization software allows you to install and use
Windows on your Intel-based Mac without requiring... Continue Reading
While Minitab 17 is currently a
Windows-only application, there are people who only have a Mac
available for the installation who also find they need to use
It is possible to run Minitab 17 on a Macintosh, though the
steps involved in the installation can seem a little daunting at
first. In the Technical Support department, we sometimes hear
reluctance in people’s voices when we throw... Continue Reading
Not long ago, I couldn’t abide
statistics. I did respect
it, but in much the same way a
gazelle respects a lion. Most of my early experiences with
statistics indicated that close encounters resulted in pain, so I
avoided further contact whenever possible.
So how is it that today I write about statistics? That’s simple:
it merely required completely reinventing the way I thought about
and approached... Continue Reading
There are many reasons why a distribution might not be
normal/Gaussian. A non-normal pattern might be caused by several
distributions being mixed together, or by a drift in time, or by
one or several outliers, or by an asymmetrical behavior, some
out-of-control points, etc.
I recently collected the scores of three different teams (the
Blue team, the Yellow team and the Pink team) after a laser... Continue Reading
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