JUNE 2013 INSIGHT

Part of a science of research lies in its analytical process. The first issue here subjects to its representativeness. Secondly, the measurement. And thirdly, the tests. Data analysis using probability and statistical techniques are just tools to help us clarify those issues. Thus, we manage to verify the differences and variances in the data.

Representativeness subjects to sampling design and showed by demographic data of the studied population. Measurement and scaling acquire representation in the form of opinion, agreeableness, or magnitude inherent within variable(s) of interest. Finally, test of differences and/or variances inferring on the propositions. Further info in slides here https://docs.google.com/file/d/0B7a64nbJZ8GBcGRDN3dZS3B1bDQ/edit?usp=sharing

     

 

STATISTICAL SIGNIFICANCE

The term statistical significance has been taken away from its real meaning since Fisher (1925) who quoted it the first time. The term seems to be abused as it connotes the practical significance. Higgs (2013) in his article, " Do We Really Need the S-word?" proposes a new word fo it. Here's the website http://www.americanscientist.org/issues/pub/do-we-really-need-the-s-word/1 for full article.

Amran Awang, PhD.

Grounded Theory in Entrepreneurship

A qualitative approach in entrepreneurship research has been proposed earlier, however the physic envy overshadowed the proposal. Among others Bygrave (1991) and lately Shepherd (2010) proposed similar approach in overcoming the quantitative methods that may mislead the unexplained entrepreneurship phenomena.

Here is a simple elaboration how to go about in executing a grounded theory approach by Jing Ke & Sarah Wenglensky (2010): http://avantgarde-jing.blogspot.com/2010/03/grounded-theory.html

Amran Awang, PhD.