May 31, 18: #AnalyticsClub #Newsletter (Events, Tips, News & more..)

[  COVER OF THE WEEK ]

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Convincing  Source

[ LOCAL EVENTS & SESSIONS]

More WEB events? Click Here

[ AnalyticsWeek BYTES]

>> Understanding the Mobile User Experience Will Help you Build a Better App by bobehayes

>> BOB in The Netherlands by bobehayes

>> The Practice of Customer Experience Management: An Overview by bobehayes

Wanna write? Click Here

[ NEWS BYTES]

>>
 North Hilo Crime Statistics for April – Big Island Now Under  Statistics

>>
 Hadoop & Big Data Analytics Market 2017-2024 Research Report – Technical Progress Under  Hadoop

>>
 Real-time Analytics Requires Modern IT Infrastructure – RTInsights (press release) (blog) Under  Streaming Analytics

More NEWS ? Click Here

[ FEATURED COURSE]

Baseball Data Wrangling with Vagrant, R, and Retrosheet

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Analytics with the Chadwick tools, dplyr, and ggplot…. more

[ FEATURED READ]

Rise of the Robots: Technology and the Threat of a Jobless Future

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What are the jobs of the future? How many will there be? And who will have them? As technology continues to accelerate and machines begin taking care of themselves, fewer people will be necessary. Artificial intelligence… more

[ TIPS & TRICKS OF THE WEEK]

Finding a success in your data science ? Find a mentor
Yes, most of us dont feel a need but most of us really could use one. As most of data science professionals work in their own isolations, getting an unbiased perspective is not easy. Many times, it is also not easy to understand how the data science progression is going to be. Getting a network of mentors address these issues easily, it gives data professionals an outside perspective and unbiased ally. It’s extremely important for successful data science professionals to build a mentor network and use it through their success.

[ DATA SCIENCE Q&A]

Q:Provide a simple example of how an experimental design can help answer a question about behavior. How does experimental data contrast with observational data?
A: * You are researching the effect of music-listening on studying efficiency
* You might divide your subjects into two groups: one would listen to music and the other (control group) wouldn’t listen anything!
* You give them a test
* Then, you compare grades between the two groups

Differences between observational and experimental data:
– Observational data: measures the characteristics of a population by studying individuals in a sample, but doesn’t attempt to manipulate or influence the variables of interest
– Experimental data: applies a treatment to individuals and attempts to isolate the effects of the treatment on a response variable

Observational data: find 100 women age 30 of which 50 have been smoking a pack a day for 10 years while the other have been smoke free for 10 years. Measure lung capacity for each of the 100 women. Analyze, interpret and draw conclusions from data.

Experimental data: find 100 women age 20 who don’t currently smoke. Randomly assign 50 of the 100 women to the smoking treatment and the other 50 to the no smoking treatment. Those in the smoking group smoke a pack a day for 10 years while those in the control group remain smoke free for 10 years. Measure lung capacity for each of the 100 women.
Analyze, interpret and draw conclusions from data.

Source

[ VIDEO OF THE WEEK]

@AnalyticsWeek Panel Discussion: Big Data Analytics

 @AnalyticsWeek Panel Discussion: Big Data Analytics

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[ QUOTE OF THE WEEK]

Information is the oil of the 21st century, and analytics is the combustion engine. – Peter Sondergaard

[ PODCAST OF THE WEEK]

@JohnNives on ways to demystify AI for enterprise #FutureOfData #Podcast

 @JohnNives on ways to demystify AI for enterprise #FutureOfData #Podcast

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[ FACT OF THE WEEK]

Every person in the world having more than 215m high-resolution MRI scans a day.

Sourced from: Analytics.CLUB #WEB Newsletter

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