Power and Sample Size

Blog posts and articles about statistical power and sample size, especially in quality improvement projects.

In my previous post, I wrote about the hypothesis testing ban in the Journal of Basic and Applied Social Psychology. I showed how P values and confidence intervals provide important information that descriptive statistics alone don’t provide. In this post, I'll cover the editors’ concerns about hypothesis testing and how to avoid the problems they describe. The editors describe hypothesis testing... Continue Reading
All processes have some variation. Some variation is natural and nothing to be concerned about. But in other cases, there is unusual variation that may need attention.  By graphing process data against an upper and a lower control limit, control charts help us distinguish natural variation from special cause variation that we need to be concerned about. If a data point falls outside the limits on... 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
It’s safe to say that most people who use statistics are more familiar with parametric analyses than nonparametric analyses. Nonparametric tests are also called distribution-free tests because they don’t assume that your data follow a specific distribution. You may have heard that you should use nonparametric tests when your data don’t meet the assumptions of the parametric test, especially the... Continue Reading
If you wanted to figure out the probability that your favorite football team will win their next game, how would you do it?  My colleague Eduardo Santiago and I recently looked at this question, and in this post we'll share how we approached the solution. Let’s start by breaking down this problem: There are only two possible outcomes: your favorite team wins, or they lose. Ties are a possibility,... Continue Reading
  In my experience, one of the hardest concepts for users to wrap their head around revolves around the Power and Sample Size menu in Minitab's statistical software, and more specifically, the field that asks for the "difference" or "difference to detect."  Let’s start with power. In statistics, the definition of power is the probability that you will correctly reject the null hypothesis when it is... Continue Reading
Stepwise regression and best subsets regression are both automatic tools that help you identify useful predictors during the exploratory stages of model building for linear regression. These two procedures use different methods and present you with different output. An obvious question arises. Does one procedure pick the true model more often than the other? I’ll tackle that question in this post. Fi... Continue Reading
Using a sample to estimate the properties of an entire population is common practice in statistics. For example, the mean from a random sample estimates that parameter for an entire population. In linear regression analysis, we’re used to the idea that the regression coefficients are estimates of the true parameters. However, it’s easy to forget that R-squared (R2) is also an estimate.... Continue Reading
Do you suffer from PAAA (Post-Analysis Assumption Angst)? You’re not alone. Checking the required assumptions for a statistical  analysis is critical. But if you don’t have a Ph.D. in statistics, it can feel more complicated and confusing than the primary analysis itself. How does the cuckoo egg data, a common sample data set often used to teach analysis of variance, satisfy the following formal... Continue Reading
A few weeks ago I looked at the number of goals that were being scored in the World Cup. At the time there were 2.9 goals per game, which was the highest since 1970. Unfortunately for spectators who enjoyed the higher scoring goals, this did not last. By the end, the average had fallen to 2.7 goals per game, the same amount scored in the 1998 World Cup. After such a high-scoring start, the goals... Continue Reading
Remember "The Little Engine That Could," the children's story about self-confidence in the face of huge challenges? In it, a train engine keeps telling itself "I think I can" while carrying a very heavy load up a big mountain. Next thing you know, the little engine has done it...but until that moment, the outcome was uncertain. It's a wonderful story for teaching kids about self-confidence. But... Continue Reading
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
We’re in the thick of the Stanley Cup playoffs, which means hockey fans are doing what seems to be every sports fan's favorite hobby...complaining about the refs! While most complaints, such as “We’re not getting any of the close calls!” are subjective and hard to get data for, there's one question that we should be able to answer objectively with a statistical analysis: Are hockey penalties... 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
I’ve written a number of blog posts about regression analysis and I've collected them here 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 model fits, making... Continue Reading
Two weeks ago Penn State and Michigan played in a quadruple-overtime thriller that almost went into a 5th overtime. Had Penn State coach Bill O’Brien kicked a field goal in the 4th overtime instead of going for it on 4th and 1, the game would have continued. But the Nittany Lions converted the 4th down (which, by the way, wasn’t a gamble) and went on to score the game winning touchdown in the 4th... Continue Reading
Even the best NHL goalies can get pulled several times each season. Do they really have cold streaks, or is a drop in save percentage on a given day part of normal random variation? My colleague Doug Gorman and I decided to find out using our favorite statistical software package.   Control Charts for Coaching Decisions We used a control chart approach to determine if coaching decisions to pull... Continue Reading
In my home, we’re huge fans of Mythbusters, the show on Discovery Channel. This fun show mixes science and experiments to prove or disprove various myths, urban legends, and popular beliefs. It’s a great show because it brings the scientific method to life. I’ve written about Mythbusters before to show how, without proper statistical analysis, it’s difficult to know when a result is statistically... Continue Reading