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Free Google Analytics Consulting Services

Google Analytics Consulting Service
We are pleased to announce that SAS Data Guru has started to offer Google Analytics Services to the public. It is free!

Services include:

1. Set up Google Analytics
2. Tutorial on Report Utlization
3. Search Engine Optimization
4. Channel Marketing Campaign
5. HTML Customization for Advanced Features

Click here to contact us.

Analytics Career Options

Career fields for Analytics:

Marketing Analytics
Clinical Analytics
Web Analytics
Risk Analytic

something

SAS Career Options

SAS Specialties from GlobalStatements.com

You can see which industries are using SAS here.

Collection of the Blogs Dedicated to SAS

SASBIOANALYST

Google Analytics Consulting Service

We are pleased to announce that SAS Data Guru has started to offer Google Analytics Services to the public.

Services include:

1. Set up Google Analytics
2. Tutorial on Report Utlization
3. Search Engine Optimization
4. Channel Marketing Campaign
5. HTML Customization for Advanced Features

Click here to contact us.

Please contact us at sasdataguru@gmail.com for more details.

Key Steps for Doing Multiple Regression

1. Build Model Using R2 or Forwarding Method
2. Check Residual Plot
3. Check Multicollinearity

Busting Loose From The Money Game

Dear readers, if you learn SAS because you want to make more money in your life, please pause and take a look at this book:

Busting Loose From the Money Game: Mind-Blowing Strategies for Changing the Rules of a Game You Can't Win by Robert Scheinfeld

What is Longitudinal Study?

"Longitudinal studies are defined as studies in which the outcome variable is repeatedly measured; i.e. the outcome variable is measured in the same individual on several different occasions. In longitudinal studies the observations of one individual over time are not independent of each other, and therefore it is necessary to apply special statistical techniques, which take into account the fact that the repeated observations of each individual are correlated. The definition of longitudinal studies(used in this book) implicates that statistical techniques like survival analyses are beyond the scope of this book. Those techniques basically are not longitudinal data analysis techniques because (in general) the outcome variable is an irreversible endpoint and therefore strictly speaking is only measured at one occasion. After the occurrence of an event no more observations are carried out on that particular subject."

Excerpt from Applied Longitudinal Data Analysis for Epidemiology, A Practical Guide by Jos W. R. Twisk

Export Excel to a Fixed Width Text File

Language R

Interesting web sites/pages related to Language R:

Sentiment Mining Video
Text Mining Infrastructure in R
tm - Text Mining Package

Text Mining Handbook

Introduction to the tm Package

textmining 1.0 - Python Text Mining Utilities

Perl Text Mine

Collection of Web Sites About Data Mining

Bing Liu: Data Mining and Text Mining Course - Fall 2007

Adam Waterworth's Cluster Algorithms for Web Applications

Collection of SAS Example Code and Data

SAS Press and SAS Documentation
Common Statistical Methods for Clinical Research with SAS Examples, Third Edition
Robert Allison's SAS/Graph Examples
UCLA Statistical Computing - SAS Textbook Example

How to Memorize p-value

When it comes to test hypotheses, nothing is more important than p-value. If you have hard time to understand or memorize the use of p-value. Here is a simple way to remember it. P-value is the probability that the null hypothesis is true. When this value is too small and below a pre-set threshold, we can confidently reject the null hypothesis. This threshold is called the significant level. This value is set by the investigator and normally is 0.05 or 0.01.

Good Tutorial for PROC SQL used in Clinical Trial Data Management

http://www.nesug.org/proceedings/nesug04/hw/hw06.pdf

Market Basket Analysis Macro

here

PROC MEANS vs PROC SUMMARY vs PROC UNIVARIATE

PROC SQL Like Statement Case Problem

proc sql;
  create table a1 as
  select *
 from a
where customer like '%Jane%'
; quit;

proc sql;
  create table a2 as
select *
from a
where customer like '%Jane%'
and visit_dte between '01jan2001:00:00:00'dt and '31jan2001:00:00:00'
; quit;

A String with Quote - Like Statement

proc sql;
  create table a1 as
  select *
  from retail
  where store_name like '%MAC''Y%'
; quit;