Blog posts and articles about testing hypotheses with the statistical method called the T-Test.

Minitab graphs are powerful tools for investigating your process
further and removing any doubt about the steps you should take to
improve it. With that in mind, you’ll want to know every feature
about Minitab graphs that can help you share and communicate your
results effectively. While many ways to modify your graph are on
the Editor menu, some of the best features become
available when you... Continue Reading

It's all too easy to make mistakes involving statistics.
Powerful statistical software can remove a lot of the difficulty
surrounding statistical calculation, reducing the risk of
mathematical errors—but correctly interpreting the results of
an analysis can be even more challenging.
No one knows that better than Minitab's technical trainers. All of our trainers
are seasoned statisticians with... Continue Reading

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There is high pressure to find low P values. Obtaining a low P
value for a hypothesis test is make or break because it can lead to
funding, articles, and prestige. Statistical significance is
everything!
My two previous posts looked at several issues related to P
values:
P values have a higher than expected false positive
rate.
The same P value from different studies can
correspond to different false... Continue Reading

The
interpretation of P values would seem to be fairly standard between
different studies. Even if two hypothesis tests study different
subject matter, we tend to assume that you can interpret a P value
of 0.03 the same way for both tests. A P value is a P value,
right?
Not so fast! While Minitab statistical software can correctly calculate all P
values, it can’t factor in the larger context of the... Continue Reading

Now that you’ve seen
how to automatically import data and run analyses in my
previous post, let’s create the Monthly Report!
I will be using a Microsoft Word Document (Office 2010) and
adding bookmarks to act as placeholders for the Graphs, statistics,
and boilerplate conclusions.
Let’s go through the steps to accomplish this:
Open up an existing report that you have previously created in
Microsoft... Continue Reading

As a member of Minitab’s Consulting and Custom Development
Services team, I get to help companies across a variety of
industries create many different types of reports for management.
These reports often need to be generated weekly or monthly. I
prefer to automate tasks like this whenever possible, so that new
or updated reports can be created without much effort. A little
investment up front can... Continue Reading

The P
value is used all over statistics, from t-tests to regression analysis. Everyone knows that you
use P values to determine statistical significance in a hypothesis test. In fact, P values often
determine what studies get published and what projects get
funding.
Despite being so important, the P value is a slippery concept
that people often interpret incorrectly. How do you
interpret P values?
In... Continue Reading

One-way
ANOVA can detect differences between the means of three or more
groups. It’s such a classic statistical analysis that it’s hard to
imagine it changing much.
However, a revolution has been under way for a while now.
Fisher's classic one-way ANOVA, which is taught in Stats 101
courses everywhere, may well be obsolete thanks to Welch’s
ANOVA.
In this post, I not only want to introduce you to... Continue Reading

My
previous post examined how an equivalence test
can shift the burden of proof when you perform hypothesis test of
the means. This allows you to more rigorously test whether the
process mean is equivalent to a target or to another mean.
Here’s another key difference: To perform the analysis, an
equivalence test requires that you first define, upfront, the size
of a practically important difference... Continue Reading

With
more options, come more decisions.
With equivalence testing added to Minitab 17, you now have more
statistical tools to test a sample mean against target value or
another sample mean.
Equivalence testing is extensively used in the biomedical field.
Pharmaceutical manufacturers often need to test whether the
biological activity of a generic drug is equivalent to that of a
brand name drug that... 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
I
worked for several years in a large manufacturing plant in which
control charts played a very important role. Virtually thousands of
SPC... Continue Reading

Transformations and non-normal distributions are typically the
first approaches considered when the when the Normality test fails
in a capability analysis. These approaches do not work when there
are extreme outliers because they both assume the data come from a
single common-cause variation distribution. But because extreme
outliers typically represent
special-cause variation, transformations... Continue Reading

Back in November, I wrote about
why running the football doesn’t cause you to win games in the
NFL. I used binary logistic regression to look at the
relationship between rush attempts (both by the lead rusher and by
the team) and wins. The results showed that the model for rush
attempts by the lead rusher and wins fit the data poorly. But the
model for team rush attempts and wins did fit the data... Continue Reading

We're
frequently asked whether Minitab has been validated by the U.S.
Food and Drug Administration (FDA) for use in the pharmaceutical
and medical device industries.
Minitab does extensive testing to validate our software
internally, but Minitab’s statistical software
is not—and cannot be—FDA-validated out-of-the-box.
Nobody's can.
It is a common misconception that software vendors can go
through a... Continue Reading

Today our company is introducing Minitab 17 Statistical
Software, the newest version of the leading software used for
quality improvement and statistics education.
So,
why should you care? Because important people in your life -- your
co-workers, your students, your kids, your boss, maybe even
you -- are afraid to analyze data.
There's no shame in that. In fact, there are pretty good
reasons for... Continue Reading

If
you regularly perform regression analysis, you know that
R2 is a statistic used to evaluate the fit of your
model. You may even know the standard definition of R2:
the percentage of variation in the response that is explained
by the model.
Fair enough. With Minitab Statistical Software doing all the heavy
lifting to calculate your R2 values, that may be all you
ever need to know.
But if you’re... Continue Reading

Using data analysis and statistics to improve business quality
has a long history. But it often seems like most of that history
involves huge operations. After all, Six Sigma originated with
Motorola, and became adopted by thousands of other businesses after
it was adopted by a little-known outfit called General
Electric.
There are many case studies and examples of how big companies
used Six Sigma... Continue Reading

Everyone loves Minitab’s
Assistant. My favorite bit, as I’ve shown with the
Gage R&R Study, is the way that the Assistant puts all the
results you need into reports that are easy to understand and
present. But it’s also pretty neat that before you ever choose what
to do in Minitab, the Assistant is ready to help you. Let’s take a
closer look at the Assistant's Graphical Analysis tools.
Help Me... Continue Reading

I’ve
written a number of blog posts about regression analysis and I
think it’s helpful to collect them in this post to create a
regression tutorial. I’ll supplement my own posts with some from my
colleagues.
This tutorial covers many aspects of regression analysis
including: choosing the type of regression analysis to use,
specifying the model, interpreting the results, determining how
well the... Continue Reading

All measurements are rounded to some degree. In most cases, you
would not want to reject normality just because the data are
rounded. In fact, the normal distribution would be a quite
desirable model for the data if the underlying distribution is
normal since it would smooth out the discreteness in the rounded
measurements.
Some normality tests reject a very high percentage of time due
to rounding... Continue Reading