[ COVER OF THE WEEK ]
Data interpretation Source
[ AnalyticsWeek BYTES]
[ NEWS BYTES]
[ FEATURED COURSE]
Data that has relevance for managerial decisions is accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations… more
[ FEATURED READ]
Python for Data Analysis is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored f… more
[ TIPS & TRICKS OF THE WEEK]
Fix the Culture, spread awareness to get awareness
Adoption of analytics tools and capabilities has not yet caught up to industry standards. Talent has always been the bottleneck towards achieving the comparative enterprise adoption. One of the primal reason is lack of understanding and knowledge within the stakeholders. To facilitate wider adoption, data analytics leaders, users, and community members needs to step up to create awareness within the organization. An aware organization goes a long way in helping get quick buy-ins and better funding which ultimately leads to faster adoption. So be the voice that you want to hear from leadership.
[ DATA SCIENCE Q&A]
Q:How do you control for biases?
A: * Choose a representative sample, preferably by a random method
* Choose an adequate size of sample
* Identify all confounding factors if possible
* Identify sources of bias and include them as additional predictors in statistical analyses
* Use randomization: by randomly recruiting or assigning subjects in a study, all our experimental groups have an equal chance of being influenced by the same bias
– Randomization: in randomized control trials, research participants are assigned by chance, rather than by choice to either the experimental group or the control group.
– Random sampling: obtaining data that is representative of the population of interest
[ VIDEO OF THE WEEK]
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[ QUOTE OF THE WEEK]
If we have data, let’s look at data. If all we have are opinions, let’s go with mine. Jim Barksdale
[ PODCAST OF THE WEEK]
[ FACT OF THE WEEK]
For a typical Fortune 1000 company, just a 10% increase in data accessibility will result in more than $65 million additional net income.