Sep 06, 18: #AnalyticsClub #Newsletter (Events, Tips, News & more..)

[  COVER OF THE WEEK ]

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Fake data  Source

[ LOCAL EVENTS & SESSIONS]

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> 5 tips to becoming a big data superhero by analyticsweekpick

>> What Are the 3 Critical Keys to Healthcare Big Data Analytics? by analyticsweekpick

>> How Big Data Is Changing The Entertainment Industry! by analyticsweekpick

Wanna write? Click Here

[ NEWS BYTES]

>>
 Insurers pay premium for cyber security experts – Financial Times Under  cyber security

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 Lawmakers Unveil Plans for Agency Telework and Cloud Security – Nextgov Under  Cloud Security

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 As VMworld nears, virtualization disrupts the cloud application ecosystem – SiliconANGLE News (blog) Under  Virtualization

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[ FEATURED COURSE]

Artificial Intelligence

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This course includes interactive demonstrations which are intended to stimulate interest and to help students gain intuition about how artificial intelligence methods work under a variety of circumstances…. more

[ FEATURED READ]

Hypothesis Testing: A Visual Introduction To Statistical Significance

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Statistical significance is a way of determining if an outcome occurred by random chance, or did something cause that outcome to be different than the expected baseline. Statistical significance calculations find their … more

[ TIPS & TRICKS OF THE WEEK]

Keeping Biases Checked during the last mile of decision making
Today a data driven leader, a data scientist or a data driven expert is always put to test by helping his team solve a problem using his skills and expertise. Believe it or not but a part of that decision tree is derived from the intuition that adds a bias in our judgement that makes the suggestions tainted. Most skilled professionals do understand and handle the biases well, but in few cases, we give into tiny traps and could find ourselves trapped in those biases which impairs the judgement. So, it is important that we keep the intuition bias in check when working on a data problem.

[ DATA SCIENCE Q&A]

Q:Explain likely differences between administrative datasets and datasets gathered from experimental studies. What are likely problems encountered with administrative data? How do experimental methods help alleviate these problems? What problem do they bring?
A: Advantages:
– Cost
– Large coverage of population
– Captures individuals who may not respond to surveys
– Regularly updated, allow consistent time-series to be built-up

Disadvantages:
– Restricted to data collected for administrative purposes (limited to administrative definitions. For instance: incomes of a married couple, not individuals, which can be more useful)
– Lack of researcher control over content
– Missing or erroneous entries
– Quality issues (addresses may not be updated or a postal code is provided only)
– Data privacy issues
– Underdeveloped theories and methods (sampling methodsÂ…)

Source

[ VIDEO OF THE WEEK]

Surviving Internet of Things

 Surviving Internet of Things

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[ QUOTE OF THE WEEK]

It is a capital mistake to theorize before one has data. Insensibly, one begins to twist the facts to suit theories, instead of theories to

[ PODCAST OF THE WEEK]

George (@RedPointCTO / @RedPointGlobal) on becoming an unbiased #Technologist in #DataDriven World #FutureOfData #Podcast

 George (@RedPointCTO / @RedPointGlobal) on becoming an unbiased #Technologist in #DataDriven World #FutureOfData #Podcast

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[ FACT OF THE WEEK]

Market research firm IDC has released a new forecast that shows the big data market is expected to grow from $3.2 billion in 2010 to $16.9 billion in 2015.

Sourced from: Analytics.CLUB #WEB Newsletter

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