Tag: data analysis

Five myths about unstructured data and five good reasons you should be analyzing it

“How can we begin to make sense of the unstructured data, when we still don’t make the most of our structured data?” said the exasperated senior manager from a large retail firm. One of the great pleasures of my job is the relationship with stude…

March Madness, Moneyball, and sports analytics

A big part of  “winning” these days (be it sports or a business) is performing analytics better than your competition.  This is demonstrated in awe-inspiring fashion in the book (and movie) “Moneyball.”  And on that topic, I’d like to show you a f…

The Human Side of Statistical Process Control: Three Applications of SAS/QC You Might Not Have Thought About

When you think of statistical process control, or SPC for short, what industry first comes to your mind? In the past 10 or 15 years, diverse industries have begun to standardize processes and administrative tasks with statistical process control. …

The Punchline: MANOVA or a Mixed Model?

So, if you were reading last week, we talked about how to structure your data for a mixed models repeated measures analysis. And as my friend Rick pointed out, there’s more than one way to go about restructuring your data (if you ask real nice, …

Discrimanant Analysis, Priors, and Fairy-Selection

A student in my multivariate class last month asked a question about prior probability specifications in discriminant function analysis:
What if I don’t know what the probabilities are in my population? Is it best to just use the default in PROC D…

Weekday Morning Quick-trick: How to Score from PROC VARCLUS

Have you used multivariate procedures in SAS and wanted to save out scores? Some procedures, such as FACTOR, CANDISC, CANCORR, PRINCOMP, and others have an OUT= option to save scores to the input data set. However, to score a new data set, or to p…