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P Value

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

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

7 Deadly Statistical Sins Even the Experts Make

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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
I’ve written a fair bit about P values: how to correctly interpret P values, a graphical representation of how they work, guidelines for using P values, and why the P value ban in one journal is a mistake. Along the way, I’ve received many questions about P values, but the questions from one reader stand out. This reader asked, why is it so easy to interpret P values incorrectly? Why is the common... 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
P-values are frequently misinterpreted, which causes many problems. I won't rehash those problems here here since my colleague Jim Frost has detailed the issues involved at some length, but the fact remains that the p-value will continue to be one of the most frequently used tools for deciding if a result is statistically significant.  You know the old saw about "Lies, damned lies, and... Continue Reading
Back when I was an undergrad in statistics, I unfortunately spent an entire semester of my life taking a class, diligently crunching numbers with my TI-82, before realizing 1) that I was actually in an Analysis of Variance (ANOVA) class, 2) why I would want to use such a tool in the first place, and 3) that ANOVA doesn’t necessarily tell you a thing about variances. Fortunately, I've had a lot more... Continue Reading
I have two young children, and I work full-time, so my adult TV time is about as rare as finding a Kardashian-free tabloid.  So I can’t commit to just any TV show. It better be a good one. I was therefore extremely excited when Netflix analyzed viewer data to find out at what point watchers get hooked on the first season of various shows. Specifically, they identified the episode at which 70% of... Continue Reading
As Halloween approaches, you are probably taking the necessary steps to protect yourself from the various ghosts, goblins, and witches that are prowling around. Monsters of all sorts are out to get you, unless they’re sufficiently bribed with candy offerings! I’m here to warn you about a ghoul that all statisticians and data scientists need to be aware of: phantom degrees of freedom. These phantoms... Continue Reading