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Stats

Blog posts and articles about statistics principles and how they apply to quality improvement methods like Lean and Six Sigma.

With another Halloween almost upon us, here's a look back at some of the posts we've written about this holiday specifically, and about various creepy things in general. I hope that you enjoy this roundup of 13 scary statistics posts...and that they won't keep you up at night! 1. How to Make Minitab Wear a Halloween Costume As Halloween nears, you can customize your Minitab interface to match the... Continue Reading
Statistical inference uses data from a sample of individuals to reach conclusions about the whole population. It’s a very powerful tool. But as the saying goes, “With great power comes great responsibility!” When attempting to make inferences from sample data, you must check your assumptions. Violating any of these assumptions can result in false positives or false negatives, thus invalidating... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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Since the release of Minitab Express in 2014, we’ve often received questions in technical support about the differences between Express and Minitab 17.  In this post, I’ll attempt to provide a comparison between these two Minitab products. What Is Minitab 17? Minitab 17 is an all-in-one graphical and statistical analysis package that includes basic analysis tools such as hypothesis testing,... Continue Reading
The ultimate goal of most quality improvement projects is clear: reducing the number of defects, improving a response, or making a change that benefits your customers. We often want to jump right in and start gathering and analyzing data so we can solve the problems. Checking your measurement systems first, with methods like attribute agreement analysis or Gage R&R, may seem like a needless waste... Continue Reading
We’ve got a plethora of case studies showing how businesses from different industries solve problems and implement solutions with data analysis. Take a look for ideas about how you can use data analysis to ensure excellence at your business! Boston Scientific, one of the world’s leading developers of medical devices, is just one organization who has shared their story. A team at their Heredia,... Continue Reading
Data mining uses algorithms to explore correlations in data sets. An automated procedure sorts through large numbers of variables and includes them in the model based on statistical significance alone. No thought is given to whether the variables and the signs and magnitudes of their coefficients make theoretical sense. We tend to think of data mining in the context of big data, with its huge... Continue Reading
In regression, "sums of squares" are used to represent variation. In this post, we’ll use some sample data to walk through these calculations. The sample data used in this post is available within Minitab by choosing Help > Sample Data, or File > Open Worksheet > Look in Minitab Sample Data folder (depending on your version of Minitab).  The dataset is called ResearcherSalary.MTW, and contains data... Continue Reading
See if this sounds fair to you. I flip a coin. Heads: You win $1.Tails: You pay me $1. You may not like games of chance, but you have to admit it seems like a fair game. At least, assuming the coin is a normal, balanced coin, and assuming I’m not a sleight-of-hand magician who can control the coin. How about this next game? You pay me $2 to play.I flip a coin over and over until it comes up heads.Your... Continue Reading
Figures lie, so they say, and liars figure. A recent post at Ben Orlin's always-amusing mathwithbaddrawings.com blog nicely encapsulates why so many people feel wary about anything related to statistics and data analysis. Do take a moment to check it out, it's a fast read. In all of the scenarios Orlin offers in his post, the statistical statements are completely accurate, but the person offering... Continue Reading
Often, when we start analyzing new data, one of the very first things we look at is whether certain pairs of variables are correlated. Correlation can tell if two variables have a linear relationship, and the strength of that relationship. This makes sense as a starting point, since we're usually looking for relationships and correlation is an easy way to get a quick handle on the data set we're... Continue Reading
Have you ever accidentally done statistics? Not all of us can (or would want to) be “stat nerds,” but the word “statistics” shouldn’t be scary. In fact, we all analyze things that happen to us every day. Sometimes we don’t realize that we are compiling data and analyzing it, but that’s exactly what we are doing. Yes, there are advanced statistical concepts that can be difficult to understand—but... Continue Reading
While some posts in our Minitab blog focus on understanding t-tests and t-distributions this post will focus more simply on how to hand-calculate the t-value for a one-sample t-test (and how to replicate the p-value that Minitab gives us).  The formulas used in this post are available within Minitab Statistical Software by choosing the following menu path: Help > Methods and Formulas > Basic... Continue Reading
If you've used our software, you’re probably used to many of the things you can do in Minitab once you’ve fit a model. For example, after you fit a response to a given model for some predictors with Stat > DOE > Response Surface > Analyze Response Surface Design, you can do the following: Predict the mean value of the response variable for new combinations of settings of the predictors. Draw... Continue Reading
Earlier this month, PLOS.org published an article titled "Ten Simple Rules for Effective Statistical Practice." The 10 rules are good reading for anyone who draws conclusions and makes decisions based on data, whether you're trying to extend the boundaries of scientific knowledge or make good decisions for your business.  Carnegie Mellon University's Robert E. Kass and several co-authors devised... Continue Reading
An outlier is an observation in a data set that lies a substantial distance from other observations. These unusual observations can have a disproportionate effect on statistical analysis, such as the mean, which can lead to misleading results. Outliers can provide useful information about your data or process, so it's important to investigate them. Of course, you have to find them first.  Finding... Continue Reading
Businesses are getting more and more data from existing and potential customers: whenever we click on a web site, for example, it can be recorded in the vendor's database. And whenever we use electronic ID cards to access public transportation or other services, our movements across the city may be analyzed. In the very near future, connected objects such as cars and electrical appliances will... Continue Reading
The last thing you want to do when you purchase a new piece of software is spend an excessive amount of time getting up and running. You’ve probably been ready to the use the software since, well, yesterday. Minitab has always focused on making our software easy to use, but many professional software packages do have a steep learning curve. Whatever package you’re using, here are three things you... Continue Reading
Suppose you’ve collected data on cycle time, revenue, the dimension of a manufactured part, or some other metric that’s important to you, and you want to see what other variables may be related to it. Now what? When I graduated from college with my first statistics degree, my diploma was bona fide proof that I'd endured hours and hours of classroom lectures on various statistical topics, including l... Continue Reading
This is an era of massive data. A huge amount of data is being generated from the web and from customer relations records, not to mention also from sensors used in the manufacturing industry (semiconductor, pharmaceutical, petrochemical companies and many other industries). Univariate Control Charts In the manufacturing industry, critical product characteristics get routinely collected to ensure... Continue Reading
Do you recall my “putting the cart before the horse” analogy in part 1 of this blog series? The comparison is simple. We all, at times, put the cart before the horse in relatively innocuous ways, such as eating your dessert before you’ve eaten your dinner, or deciding what to wear before you’ve been invited to the party. But performing some tasks in the wrong order, such as running a statistical... Continue Reading