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CBAP certification: A high-profile credential for business analysts

CIO Business Intelligence

IIBA is a nonprofit professional association founded in 2003 to promote the field of business analysis. There must be a measurable learning objective or set of objectives that are directly applicable to changing the behavior or improving the skills of a business analyst.

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Using Empirical Bayes to approximate posteriors for large "black box" estimators

The Unofficial Google Data Science Blog

Posteriors are useful to understand the system, measure accuracy, and make better decisions. Methods like the Poisson bootstrap can help us measure the variability of $t$, but don’t give us posteriors either, particularly since good high-dimensional estimators aren’t unbiased. Figure 4 shows the results of such a test.

KDD 40
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Multiplicity: Succeed Awesomely At Web Analytics 2.0!

Occam's Razor

My first eMetrics summit was June 2003 and as a young inexperienced person new in the field it was a great learning experience (eMetrics in Santa Barbara were the best!). Five different sources of data, that require you to have multiple tools to measure success. ." Ok let me explain. Two New, Interesting & Non-Obvious Tools.

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Humans-in-the-loop forecasting: integrating data science and business planning

The Unofficial Google Data Science Blog

For example, we may prefer one model to generate a range, but use a second scenario-based model to “stress test” the range. If the alternate model is plausible with a small probability, then we’d like to see that the “stress test” forecast scenario still falls inside the prediction interval generated from our preferred model.

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The trinity of errors in applying confidence intervals: An exploration using Statsmodels

O'Reilly on Data

We use the diagnostic test results of our regression model to support the reasons why CIs should not be used in financial data analyses. The probability of an event should be measured empirically by repeating similar experiments ad nauseam —either in reality or hypothetically. Jaynes, Cambridge University Press, 2003.