The search for data has been a cognitive process much longer in our psyche than carefully understanding and using right measure. We are easily fooled by the argument of how we explain by quoting or not quoting the data source provided by others, often not even knowing the veracity of the source, and willingly or easily believe. However, we hardly spend enough time to question, how is the measure defined?
The famous problems of people getting confused in regard to use of joint probability vs. conditional probability, or when to use mean, median or mode, when to use arithmetic mean vs. geometric mean vs. harmonic mean are enough to make people pass clueless, and often times even above college level educated people.
This is complaining about people. The point I am driving is that it is a special cognitive process that has to be trained.
Being analytical is the next higher level of cognition and it requires systematic thinking and systematic statistical principles and concepts. While every one would like to be analytical in thinking, deciding with least bias and knowing and keeping the amount of error in prediction to be minimal is a deeper cognitive process.
Also, we all know how important the measurement, OBP was in the Moneyball assignment, and in fact, it was the organizational strategic metric.
So once the most important measurement is identified for the analytical works, and its full logic tree, or "hypotheses tree" or the "MECE tree" are drawn, each of the end notes are called data analytics strategies, and all the elements needed to each one of the end nodes are the ones we need to analyze the totality of the analytics project.
Where do data come from?:
In terms of locating the right data, there are four sources.
- Application/Registration/Inquiry data – Prospect data
- Transaction data
- Third party – syndicated data (geo-demographic, lifestyle, attitudinal, behavioral data)
- Survey data (special enterprise initiated vs. existing panels)
Continue with Part 3….
Ref: Joint-Marginal-ConditionalProbabilities and Bayes Theorem – From httpocw.metu.edu.tr