T-Test Example

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

by Jasmin Wong, guest blogger The combination of statistical methods and injection moulding simulation software gives manufacturers a powerful way to predict moulding defects and to develop a robust moulding process at the part design phase.  CAE (computer-aided engineering) is widely used in the injection moulding industry today to improve product and mould designs as well as to resolve or... Continue Reading
I’ve written about the importance of checking your residual plots when performing linear regression analysis. If you don’t satisfy the assumptions for an analysis, you might not be able to trust the results. One of the assumptions for regression analysis is that the residuals are normally distributed. Typically, you assess this assumption using the normal probability plot of the residuals. Are... Continue Reading
I got lost a lot as a child. I got lost at malls, at museums, Christmas markets, and everywhere else you could think of. Had it been in fashion to tether children to their parents at the time, I'm sure my mother would have. As an adult, I've gotten used to using a GPS device to keep me from getting lost. The Assistant in Minitab is like your GPS for statistics. The Assistant is there to provide you... Continue Reading
Using statistical techniques to optimize manufacturing processes is quite common now, but using the same approach on social topics is still an innovative approach. For example, if our objective is to improve student academic performances, should we increase teachers wages or would it be better to reduce the number of students in a class? Many social topics (the effect of increasing the minimum... Continue Reading
Previously, I showed why there is no R-squared for nonlinear regression. Anyone who uses nonlinear regression will also notice that there are no P values for the predictor variables. What’s going on? Just like there are good reasons not to calculate R-squared for nonlinear regression, there are also good reasons not to calculate P values for the coefficients. Why not—and what to use instead—are the... Continue Reading
by The Discrete Sharer, guest blogger As Minitab users, many of us have found staged control charts to be an effective tool to quantify and demonstrate the “before and after” state of our process improvement activities. However, have you ever considered using them to demonstrate the effects of changes to compensation/incentive plans for your employees?  Here's an example of how a mid-sized... Continue Reading
Screening experimental designs allow you to study a very large number of factors in a very limited number of runs. The objective is to focus on the few factors that have a real effect and eliminate the effects that are not significant. This is often the initial typical objective of any experimenter when a DOE (design of experiments) is performed. Table of Factorial Designs Consider the table below.... Continue Reading
In Part I and Part II we learned about the experiment and the survey, respectively. Now we turn our attention to the results... Our first two participants, Danielle and Sheryl, enter the conference room and are given blindfolds as we explain how the experiment will proceed.  As we administer the tasting, the colors of the wine are obvious but we don't know the true types, which have been masked... Continue Reading
In Blind Wine Part I, we introduced our experimental setup, which included some survey questions asked ahead of time of each participant. The four questions asked were: On a scale of 1 to 10, how would you rate your knowledge of wine? How much would you typically spend on a bottle of wine in a store? How many different types of wine (merlot, riesling, cabernet, etc.) would you buy regularly (not as... Continue Reading
After upgrading to the latest and greatest version of our statistical software, Minitab 17, some users have contacted tech support to ask "Wait a minute, where is that Two-Way ANOVA option in Minitab 17?"  The answer is that it’s not there. That’s right! The 2-Way ANOVA option that was available in Minitab 16 and prior versions was removed from Minitab 17.Why would this feature be removed from the... Continue Reading
We received the following question via social media recently: I am using Minitab 17 for ANOVA. I calculated the mean and standard deviation for these 15 values, but the standard deviation is very high. If I delete some values, I can reduce the standard deviation. Is there an option in Minitab that will automatically indicate values that are out of range and delete them so that the standard... Continue Reading
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