Blog posts and articles about how to use and interpret the P Value statistic in quality improvement efforts.

Design of Experiments (DOE) is the perfect tool to efficiently
determine if key inputs are related to key outputs. Behind the
scenes, DOE is simply a regression analysis. What’s not simple,
however, is all of the choices you have to make when planning your
experiment. What X’s should you test? What ranges should you select
for your X’s? How many replicates should you use? Do you need
center... Continue Reading

In the great 1971 movie Willy Wonka and the Chocolate
Factory, the reclusive owner of the Wonka Chocolate Factory
decides to place golden tickets in five of his famous chocolate
bars, and allow the winners of each to visit his factory with a
guest. Since restarting production after three years of silence, no
one has come in or gone out of the factory. Needless to say, there
is enormous interest in... Continue Reading

In my last post, we took the red pill and dove
deep into the unarguably fascinating and uncompromisingly
compelling world of the matrix plot. I've stuffed this post with
information about a topic of marginal interest...the marginal
plot.
Margins are important. Back in my English composition days, I
recall that margins were particularly prized for the inverse linear
relationship they maintained with... Continue Reading

Time series data is proving to be very useful these days in a
number of different industries. However, fitting a specific model
is not always a straightforward process. It requires a good look at
the series in question, and possibly trying several different
models before identifying the best one. So how do we get there? In
this post, I'll take a look at how we can examine our data and get
a feel... Continue Reading

There
may not be a situation more perilous than being a character on
Game of Thrones. Warden of the North, Hand of
the King, and apparent protagonist of the entire series? Off with
your head before the end of the first season! Last male heir of a
royal bloodline? Here, have a pot of molten gold poured on your
head! Invited to a wedding? Well, you probably know what happens at
weddings in the show. ... Continue Reading

In part 2 of this series, we used graphs and tables to see
how individual factors affected rates of patient participation
in a cardiac rehabilitation program. This initial look at the data
indicated that ease of access to the hospital was a very important
contributor to patient participation.
Given
this revelation, a bus or shuttle service for people who do not
have cars might be a good way to... Continue Reading

Analysis of variance (ANOVA) can determine whether the means of
three or more groups are different. ANOVA uses F-tests to
statistically test the equality of means. In this post, I’ll show
you how ANOVA and F-tests work using a one-way ANOVA example.
But wait a minute...have you ever stopped to wonder why you’d
use an analysis of variance to determine whether
means are different? I'll also show how... Continue Reading

by Laerte de Araujo Lima, guest blogger
The NBA's 2015-16 season will be one for the history books. Not
only was it the last season of Kobe Bryan,
who scored 60 points in his final game, but the Golden State
Warriors set
a new wins record, beating the previous record set by 1995-96
Chicago Bulls.
The
Warriors seem likely to take this season's NBA title, in large part
thanks to the performance of... Continue Reading

In statistics, t-tests are a type of hypothesis test that allows
you to compare means. They are called t-tests because each t-test
boils your sample data down to one number, the t-value. If you
understand how t-tests calculate t-values, you’re well on your way
to understanding how these tests work.
In this series of posts, I'm focusing on concepts rather than
equations to show how t-tests work.... Continue Reading

T-tests are handy hypothesis tests in statistics when you want to
compare means. You can compare a sample mean to a hypothesized or
target value using a one-sample t-test. You can compare the means
of two groups with a two-sample t-test. If you have two groups with
paired observations (e.g., before and after measurements), use the
paired t-test.
How do t-tests work? How do t-values fit in? In this... Continue Reading

About
a year ago, a reader asked if I could try to explain
degrees of freedom in statistics. Since then,
I’ve been circling around that request very cautiously, like it’s
some kind of wild beast that I’m not sure I can safely wrestle to
the ground.
Degrees of freedom aren’t easy to explain. They come up in many
different contexts in statistics—some advanced and complicated. In
mathematics, they're... Continue Reading

P values have been around for nearly a century and they’ve been
the subject of criticism since their origins. In recent years, the
debate over P values has risen to a fever pitch. In particular,
there are serious fears that P values are misused to such an extent
that it has actually damaged science.
In March 2016, spurred on by the growing concerns, the American
Statistical Association (ASA) did... Continue Reading

Probability. It's really the heart and soul of most statistical
analyses. Anytime you get a
p-value, you're dealing with a probability. The probability is
telling you how likely it was (or will be) for an event to occur.
It has numerous applications across a wide variety of areas. But
today I want to focus on the probability of a specific event.
A basketball tournament.
I’ll be using the Sagarin... Continue Reading

I am a bit of an Oscar fanatic.
Every year after the ceremony, I religiously go online to find out
who won the awards and listen to their acceptance speeches. This
year, I was so chuffed to learn that Leonardo Di Caprio
won his first Oscar for his performance in The Revenant in
the 88thAcademy
Awards—after five nominations in previous ceremonies. As a
longtime Di Caprio fan, I still remember... Continue Reading

What is an interaction? It’s when the effect of one factor
depends on the level of another factor. Interactions are important
when you’re performing ANOVA, DOE, or a regression analysis.
Without them, your model may be missing an important term that
helps explain variability in the response!
For example, let’s consider 3-point shooting in the NBA. We
previously saw that the number of 3-point... Continue Reading

In my last post, I looked at
viewership data for the five seasons of HBO’s hit series Game of
Thrones. I
created a time series plot in Minitab that showed how
viewership rose season by season, and how it varied episode by
episode within each season.
My next step is to fit a statistical model to the data, which
I hope will allow me to predict the viewing numbers for future
episodes.
I am going to... Continue Reading

If you want to convince someone that at least a basic
understanding of statistics is an essential life skill, bring up
the case of Lucia de Berk. Hers is a story that's too awful to be
true—except that it is completely true.
A
flawed analysis irrevocably altered de Berk's life and kept her
behind bars for five years, and the fact that this analysis
targeted and harmed just one person makes it more... Continue Reading

In the world of linear models, a hierarchical model contains all
lower-order terms that comprise the higher-order terms that also
appear in the model. For example, a model that includes the
interaction term A*B*C is hierarchical if it includes these terms:
A, B, C, A*B, A*C, and B*C.
Fitting the correct regression model can be as
much of an art as it is a science. Consequently, there's not always
a... Continue Reading

How deeply has statistical content from Minitab blog posts (or
other sources) seeped into your brain tissue? Rather than submit a
biopsy specimen from your temporal lobe for analysis, take this
short quiz to find out. Each question may have more than one
correct answer. Good luck!
Which
of the following are famous figure skating pairs, and which are
methods for testing whether your data follow a... Continue Reading

If you perform linear regression analysis, you might need to
compare different regression lines to see if their constants and
slope coefficients are different. Imagine there is an established
relationship between X and Y. Now, suppose you want to determine
whether that relationship has changed. Perhaps there is a new
context, process, or some other qualitative change, and you want to
determine... Continue Reading