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T-Test Example

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

Control charts are some of the most useful tools in statistical science. They track process statistics over time and detect when the mean or standard deviation change from what they have been. The signals that control charts send about special causes can help you zero in on the fastest ways to improve any process, whether you’re making tires, turbines, or trying to improve patient care. I’ve menti... Continue Reading
There is more than just the p value in a probability plot—the overall graphical pattern also provides a great deal of useful information. Probability plots are a powerful tool to better understand your data. In this post, I intend to present the main principles of probability plots and focus on their visual interpretation using some real data. In probability plots, the data density distribution... Continue Reading
A recent study has indicated that female-named hurricanes kill more people than male hurricanes. Of course, the title of that article (and other articles like it) is a bit misleading. The study found a significant interaction between the damage caused by the storm and the perceived masculinity or femininity of the hurricane names. So don’t be confused by stories that suggest all... Continue Reading
by Matthew Barsalou, guest blogger Programs such as the Minitab Statistical Software make hypothesis testing easier; but no program can think for the experimenter. Anybody performing a statistical hypothesis test must understand what p values mean in regards to their statistical results as well as potential limitations of statistical hypothesis testing. A p value of 0.05 is frequently used during... Continue Reading
In Minitab, the Assistant menu is your interactive guide to choosing the right tool, analyzing data correctly, and interpreting the results. If you’re feeling a bit rusty with choosing and using a particular analysis, the Assistant is your friend! Previously, I’ve written about the new linear model features in Minitab 17. In this post, I’ll work through a multiple regression analysis example and... 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
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