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Home Archive by category "Analytics"

Category: Analytics

Various statistical analysis performed over the years with tools such as SPSS, SYSTAT, SAS, Excel, Python,R, etc. While the more interesting /complicated multivariate techniques are incredibly insightful, often simple cross-tabs, and a good design, can be used to find an answer to the problem at hand.

Time and Money savings Calculator

Time and Money savings Calculator

A YouTube subscriber recently reminded me I’d made this Time and Money savings Calculator

Here’s the video showing how to use the Time and Money savings Calculator

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

SPSS macro performs K-means Cluster analysis and does the “heavy lifting”

SPSS macroI frequently play around with multivariate techniques like K-means cluster analysis in SPSS.  There were some big holes in the SPSS procedure that performs cluster analysis so wrote an SPSS Macro to automate what I wanted to be done.    Below is a  quick demo of the macro in use. It can really save a bunch of time!  A few things mine does differently is:

  1. assigns labels to the segments (these will be changed later but butter than just a 1,2,3)
  2. Computes frequencies on the size of the segments (Why SPSS doesn’t do this automatically is beyond me)
  3. Color-codes and merges the significance testing in with the profile-plot showing what is different.

SPSS macro performing K-means Cluster analysis

https://www.youtube.com/watch?v=QUDfYOb6qII

 

Moving data from one column to many; Parsing a variable using an SPSS macro

one column to many

Older online vendor tools and databases would frequently put multi-select questions into one column having a pipe,tab,semicolon or comma delimiter (what was real fun is when they would use a comma for a delimiter in a CSV file).

This can be very problematic in nearly any tool. In this video I demonstrate how easy it can be to move data from one column to many with an SPSS macro.

Move one column to many

https://www.youtube.com/watch?v=ldoPLOFyVAI

Here is the SPSS macro demonstrated in the video:

 
*///////////////.
DEFINE !Parse (Var !TOKENS (1)  / Stem !TOKENS (1) /Del !TOKENS (1))
STRING #(A1000).
VECTOR !Stem(25A500).
COMPUTE #=CONCAT(RTRIM(!Var),!Del).
COMPUTE #cnt=1.
LOOP IF INDEX(#,!Del)>0.
COMPUTE !Stem(#cnt)=SUBSTR(#,1,INDEX(#,!Del)-1).
COMPUTE #cnt=#cnt + 1.
COMPUTE #=SUBSTR(#,INDEX(#,!Del)+1).
Var width !Concat(!Stem,1) to !Concat(!Stem,25) (10).
END LOOP.
EXECUTE.
!ENDDEFINE.
*///////////////.
/* !Parse Var=NAIC_All Stem=NAIC  Del=";".