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Tips and Techniques for Statistics and Quality Improvement

Blog posts and articles about using Minitab software in quality improvement projects, research, and more.

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
by Matthew Barsalou, guest blogger Control charts plot your process data to identify and distinguish between common cause and special cause variation. This is important, because identifying the different causes of variation lets you take action to make improvements in your process without over-controlling it. When you create a control chart, the software you're using should make it easy to see where... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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You often hear the data being blamed when an analysis is not delivering the answers you wanted or expected. I was recently reminded that the data chosen or collected for a specific analysis is determined by the analyst, so there is no such thing as bad data—only bad analysis.  This made me think about the steps an analyst can take to minimise the risk of producing analysis that fails to answer... 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
It’s not easy to get data ready for analysis. Sometimes, data that include all the details we want aren’t clean enough for analysis. Even stranger, sometimes the exact opposite can be true: Data that are convenient to collect often don’t include the details that we want when we analyze them. Let’s say that you’re looking at the documentation for the National Health and Nutrition Examination Survey... Continue Reading
Technology is very much part of our lives nowadays. We use our smartphones to have video calls with our friends and family, and watch our favourite TV shows on tablets. Technology has also transformed the fitness industry with the increasing popularity of fitness trackers. Recently, I got myself a fitness watch and it's becoming my favourite gadget. It can track how many steps I’ve taken, my... 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
Remember the classic science fiction film The Matrix? The dark sunglasses, the leather, computer monitors constantly raining streams of integers (inexplicably in base 10 rather than binary or hexadecimal)? And that mind-blowing plot twist when Neo takes the red pill from Morpheus' outstretched hand? Well to me, there's one thing even more mind-blowing than the plot of the Matrix: the Matrix Plot.... Continue Reading
Time series data is proving to be very useful these days in a number of different industries. However, fitting a specific model is not always a straightforward process. It requires a good look at the series in question, and possibly trying several different models before identifying the best one. So how do we get there? In this post, I'll take a look at how we can examine our data and get a feel... Continue Reading
There may not be a situation more perilous than being a character on Game of Thrones. Warden of the North, Hand of the King, and apparent protagonist of the entire series? Off with your head before the end of the first season! Last male heir of a royal bloodline? Here, have a pot of molten gold poured on your head! Invited to a wedding? Well, you probably know what happens at weddings in the show. ... Continue Reading
By looking at the data we have about 500 cardiac patients, we've learned that easy access to the hospital and good transportation are key factors influencing participation in a rehabilitation program. Past data shows that each month, about 15 of the patients discharged after cardiac surgery do not have a car. Providing transportation to the hospital might make these patients more likely to join... Continue Reading
In part 2 of this series, we used graphs and tables to see how individual factors affected rates of patient participation in a cardiac rehabilitation program. This initial look at the data indicated that ease of access to the hospital was a very important contributor to patient participation. Given this revelation, a bus or shuttle service for people who do not have cars might be a good way to... 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
What does the eyesight of a homeless person have in common with complications from dental anesthesia?  Or with reducing side-effects from cancer? Or monitoring artificial hip implants? These are all subjects of recently published studies that use statistical analyses in Minitab to improve healthcare outcomes. And they're a good reminder  that when we improve the quality of healthcare for others, we... 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
My previous post covered the initial phases of a project to attract and retain more patients in a cardiac rehabilitation program, as described in a 2011 Quality Engineering article. A Pareto chart of the reasons enrolled patients left the program indicated that the hospital could do little to encourage participants to attend a greater number of sessions, so the team focused on increasing initial... Continue Reading
Over the past year I've been able to work with and learn from practitioners and experts who are using data analysis and Six Sigma to improve the quality of healthcare, both in terms of operational efficiency and better patient outcomes. I've been struck by how frequently a very basic analysis can lead to remarkable improvements, but some insights cannot be attained without conducting more... 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
For one reason or another, the response variable in a regression analysis might not satisfy one or more of the assumptions of ordinary least squares regression. The residuals might follow a skewed distribution or the residuals might curve as the predictions increase. A common solution when problems arise with the assumptions of ordinary least squares regression is to transform the response... Continue Reading