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Regression Analysis

Blog posts and articles about regression analysis methods applied to Lean and Six Sigma projects.

If you were among the 300 people who attended the first-ever Minitab Insights conference in September, you already know how powerful it was. Attendees learned how practitioners from a wide range of industries use data analysis to address a variety of problems, find solutions, and improve business practices. In the coming weeks and months, we will share more of the great insights and guidance shared... Continue Reading
Face it, you love regression analysis as much as I do. Regression is one of the most satisfying analyses in Minitab: get some predictors that should have a relationship to a response, go through a model selection process, interpret fit statistics like adjusted R2 and predicted R2, and make predictions. Yes, regression really is quite wonderful. Except when it’s not. Dark, seedy corners of the data... Continue Reading

7 Deadly Statistical Sins Even the Experts Make

Do you know how to avoid them?

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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
Today, September 16, is World Ozone Day. You don't hear much about the ozone layer any more. In fact, if you’re under 30, you might think this is just another trivial, obscure observance, along the lines of International Dot Day (yesterday) or National Apple Dumpling Day (tomorrow). But there’s a good reason that, almost 30 years ago, the United Nations designated today to as a day to raise... Continue Reading
You’ve performed multiple linear regression and have settled on a model which contains several predictor variables that are statistically significant. At this point, it’s common to ask, “Which variable is most important?” This question is more complicated than it first appears. For one thing, how you define “most important” often depends on your subject area and goals. For another, how you collect... Continue Reading
There may be huge potential benefits waiting in the data in your servers. These data may be used for many different purposes. Better data allows better decisions, of course. Banks, insurance firms, and telecom companies already own a large amount of data about their customers. These resources are useful for building a more personal relationship with each customer. Some organizations already use... Continue Reading
The college football season is here, and this raises a very important question: Is Alabama going to be undefeated when they win the national championship, or will they lose a regular-season game along the way? Okay, so it's not a given that Alabama is going to win the championship this year, but when you've won 4 of the last 7 you're definitely the odds-on favorite. However, what if we wanted to take... Continue Reading
If you’re in the market for statistical software, there are many considerations and more than a few options for you to evaluate. Check out these seven questions to ask yourself before choosing statistical software—your answers should help guide you towards the best solution for your needs! 1. Who uses statistical software in your organization? Are they expert statisticians, novices, or a mix of both?... 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
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
Statistics is all about modelling. But that doesn’t mean strutting down the catwalk with a pouty expression.  It means we’re often looking for a mathematical form that best describes relationships between variables in a population, which we can then use to estimate or predict data values, based on known probability distributions. To aid in the search and selection of a “top model,” we often utilize... Continue Reading
You need to consider many factors when you’re buying a used car. Once you narrow your choice down to a particular car model, you can get a wealth of information about individual cars on the market through the Internet. How do you navigate through it all to find the best deal?  By analyzing the data you have available.   Let's look at how this works using the Assistant in Minitab 17. With the... Continue Reading
Design of Experiments (DOE) is the perfect tool to efficiently determine if key inputs are related to key outputs. Behind the scenes, DOE is simply a regression analysis. What’s not simple, however, is all of the choices you have to make when planning your experiment. What X’s should you test? What ranges should you select for your X’s? How many replicates should you use? Do you need center... Continue Reading
In my last post, we took the red pill and dove deep into the unarguably fascinating and uncompromisingly compelling world of the matrix plot. I've stuffed this post with information about a topic of marginal interest...the marginal plot. Margins are important. Back in my English composition days, I recall that margins were particularly prized for the inverse linear relationship they maintained with... 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
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
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
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