Regression tree on employee satisfaction data helped identify priorities

Regression Trees

While multiple regression is a great tool for analyzing data, most clients (sadly) have a hard time “getting” it.  Over the years of working with corporate executives I have found that regression trees are much easier for non-stat people to understand.

Below is a tree from SYSTAT that was created from data collected by employees in annual employee satisfaction study.  Putting the tree together and making it “pretty” helped C-level executives understand what we needed to work on.  Please be sure you transform your data before running your analtyics.  Employee satisfaction data nearly always has negative skewness.

regrssion tree

 

Employee satisfaction is a fascinating topic.  A decent introduction and review  can be found in this book:

Here’s a great book to get ideas on conveying data visually

Report Generation- Crank out automated reports!

report generation

Report Generation

In market research I would very frequently have to crank out a ton of different versions of reports for a given study.  In the corporate world, like it or not, PowerPoint is still king.  :(   By building a generic template I was able to drastically speed-up my report generation.

Setting up the template takes a little time at first however, in the long run, it will save you an amazing amount of time!

There is a lot more I automated however having a flexible template is always a great place to start!

Psychological affects of the slope- Practical example on my own weight loss

Psychological affects of the slope

I’ve been on a (much needed) diet since mid January.  While my progress is going really well, I was looking at the graph I’d made and was surprised how much my attitude changed when I simply changed the ratio of one axis.  I have been working in stats for ~20 years and I’m well aware of how people purposely try and lie/mislead with graphs so I didn’t think changing the ratio would affect my mood but damn was I wrong!

In the below two graphs they both have the exact same slope & R-square however, the one the left is wider (making it seem like my weight-loss is going slower), than the one on the right.

Which graph would you rather be using to see your progress?   And, yes, I know I truncated the graph at 180.  While weight is a “scale” variable (excuse the pun) I have an ideal weight I’m aiming for.  Besides, nobody wan’ts to see me at 100 lbs.

Psychological affects of the slope

Psychological affects of the slope
This experiment reminded me of Dan Ariely’s books. This one is exceptionally well written and thought provoking.