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
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
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
you ever wonder why statistical analyses and concepts often have
such weird, cryptic names?
One conspiracy theory points to the workings of a secret
committee called the ICSSNN. The International Committee for
Sadistic Statistical Nomenclature and Numerophobia was formed
solely to befuddle and subjugate the masses. Its mission: To select
the most awkward, obscure, and confusing name possible... Continue Reading
The language of statistics is a funny thing, but there usually
isn't much to laugh at in the consequences that can follow when
misunderstandings occur between statisticians and
non-statisticians. We see these consequences frequently in the
media, when new studies—that usually contradict previous ones—are
breathlessly related, as if their findings were incontrovertible
Similar, though less... Continue Reading
2 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
The common... 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
The season of change is upon us here at Minitab's World
Headquarters. The air is crisp and clear and the landscape is
ablaze in vibrant fall colors. As I drove to work one recent
morning, I couldn't help but soak in the beauty surrounding me and
think, "Too bad everything they taught me as a kid was a lie."
see, as a boy growing up in New Hampshire, I was told that the
sublime beauty of autumn... Continue Reading
Pareto charts are a special type of bar chart you can use to
prioritize almost anything. This makes them very useful in making
sound decisions. For example, if you have several possible quality
improvement projects, but not enough time or people to do them all
now, you can use a Pareto chart to identify which projects have the
most potential for making meaningful improvement.
Pareto charts look... 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
If your work involves quality improvement, you've at least
heard of Design of Experiments (DOE). You probably know
it's the most efficient way to optimize and improve your process.
But many of us find DOE intimidating, especially if it's not a tool
we use often. How do you select an appropriate design, and ensure
you've got the right number of factors and levels? And after you've
gathered your... Continue Reading
With another Halloween almost upon us, here's a look back at
some of the posts we've written about this holiday specifically,
and about various creepy things in general. I hope that you enjoy
this roundup of 13 scary statistics posts...and that they won't
keep you up at night!
1. How to Make Minitab Wear a Halloween Costume
As Halloween nears, you can customize your Minitab interface to
match the... 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
We hosted our first-ever Minitab Insights conference in
September, and if you were among the attendees, you already know
the caliber of the speakers and the value of the information they
shared. Experts from a wide range of industries offered a lot of
great lessons about how they use data analysis to improve business
practices and solve a variety of problems.
I blogged earlier about five key...Continue Reading
If you were among the 300 people who attended the first-ever
Minitab Insights conference in September, you already know how
powerful it was. Attendees learned how practitioners from a
wide range of industries use data analysis to address a variety of
problems, find solutions, and improve business practices.
In the coming weeks and months, we will share more of the great
insights and guidance shared... Continue Reading
There may be huge potential benefits waiting in the data in your
servers. These data may be used for many different purposes. Better
data allows better decisions, of course. Banks, insurance firms,
and telecom companies already own a large amount of data about
their customers. These resources are useful for building a more
personal relationship with each customer.
Some organizations already use... Continue Reading
If you’re in the market for statistical software, there are many
considerations and more than a few options for you to evaluate.
Check out these seven questions to ask yourself before choosing
statistical software—your answers should help guide you towards the
best solution for your needs!
1. Who uses statistical software in your organization?
Are they expert statisticians, novices, or a mix of both?... Continue Reading
So the data you nurtured, that you worked so hard to format and
make useful, failed the normality test.
Time to face the truth: despite your best efforts, that data set
is never going to measure up to the assumption you may
have been trained to fervently look for.
Your data's lack of normality seems to make it poorly suited for
analysis. Now what?
Take it easy. Don't get uptight. Just let your data... Continue Reading
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