Statistically significance in A/B Testing

A/B Tests in Marketing – Sample Size and Significance using R

A/B Tests in Marketing – Sample Size and Significance using R

Hypothesis Test: Difference Between Proportions
http://stattrek.com/hypothesis-test/difference-in-proportions.aspx

G-test vs T-test, which is better for A/B testing?
http://stats.stackexchange.com/questions/25209/difference-between-g-test-and-t-test-and-which-should-be-used-for-a-b-testing

Awell-known A/B test tutorial:
http://elem.com/~btilly/effective-ab-testing/

How do you determine what is “statistically significant” when looking at the results of an A/B test?
http://www.quora.com/How-do-you-determine-what-is-statistically-significant-when-looking-at-the-results-of-an-A-B-test

For better understanding, one should take course in statistical inference:
https://www.edx.org/course/uc-berkeleyx/uc-berkeleyx-stat2-3x-introduction-1533#.VEVFCSSfiaB

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Choosing a Machine Learning Classifier

http://blog.echen.me/2011/04/27/choosing-a-machine-learning-classifier/

Translation in Chinese: http://zhan.renren.com/pandalearning?tagId=109553&from=template&checked=true


 

Data Science: What are the best blogs for data miners and data scientists to read?

http://www.quora.com/Data-Science/What-are-the-best-blogs-for-data-miners-and-data-scientists-to-read

How to hire data scientists and get hired as one

Gigaom

As you might have heard before if you read McKinsey reports, the New York Times or just about any technology news site, data scientists are in high demand. Heck, the Harvard Business Review called it the sexiest job of the 21st century. But landing a gig as a data scientist isn’t easy — especially a top-notch gig at a major web or e-commerce company where merely talented people are a dime a dozen.

However, companies are starting to talk openly about what they look for in data scientists, including the skills someone should have and what they’ll need to know to survive an interview. I spent a day at the Predictive Analytics World conference on Monday and heard both Netflix and Orbitz give their two cents. That’s also the same day Hortonworks published a blog post about how to build a data science team.

Granted that…

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Topics need to catch up with

1. survival model:

2. Basic statistics in R:

3. Time series

4. Useful personal website: