​​#vizualization #statistics

​​Fair Regression for Health Care Spending

What happens, if fairness built into the objective function for continuous outcomes & see large improvements in group undercompensation?

This is the most interesting & potentially impactful analysis of fairness in #ML for #healthcare, which can lead to significant improvement in the life of millions.

ArXiV: https://arxiv.org/abs/1901.10566
GitHub: https://github.com/zinka88/Fair-Regression

#statistics #regression

​​Why Financial Planning is Exciting… At Least for a Data Scientist

Great introduction into the finance world and what data scientist can lack diving into the topic.

Link: https://eng.uber.com/financial-planning-for-data-scientist/

#Financial #statistics #Uber

Probabilistic foundations of econometrica: part 1

Great intro into #statistics basics.

Link: https://freakonometrics.hypotheses.org/57649

#beginner #novice #entrylevel

Analyzing Experiment Outcomes: Beyond Average Treatment Effects

Good #statistics article on why tail distribution and #experimentdesign matters. Quantile treatment effects (QTEs) helps to capture the inherent heterogeneity in treatment effects when riders and drivers interact within the #Uber marketplace.

Link: https://eng.uber.com/analyzing-experiment-outcomes/

​​Pseudo-extended Markov chain Monte Carlo

Pseudo-Extended #MC for easier sampling from multimodal posteriors. Extend the target distribution and then run your favourite sampler (f.e. #HMC).

ArXiV: https://arxiv.org/abs/1708.05239

#statistics

​​Important article in Nature about statistical significance

Scientists rise up against statistical significance — about motion to move from widely using and quoting statistical significance to confindence intervals.

Link: https://www.nature.com/articles/d41586-019-00857-9

#statistics #statsignificance #nature #science

Ranking Items With Star Ratings and How Not To Sort By Average Rating

Two absolute must read articles for proper sorting handling. Sorting items with just an average score is wrong and there is some good classic statistics explanation why.

Link: https://www.evanmiller.org/ranking-items-with-star-ratings.html
Link2: https://www.evanmiller.org/how-not-to-sort-by-average-rating.html

#Statistics #rating #scoring #ranking

The female problem: how male bias in medical trials ruined women's health

Intersting article on #bias in #medical trials and how proper #statistics training is still important.

Link: https://www.theguardian.com/lifeandstyle/2019/nov/13/the-female-problem-male-bias-in-medical-trials

📚Guest post on great example of book abandonment at GoodReads

An excellent new article from Gwern on analyzing abandoned (hard to finish, hard to read) books on Goodreads. This write up includes step by step instructions with source code, even the way he parsed the data from the website without an API.

It’s a shame analysis like this does not come from an online book subscription service like Bookmate or MyBook. They have vastly superior datasets and many able data scientists. I am quite sure amazon kindle team does prepare internal reports like that for some evil business purposes, but that’s a whole different story.

During my time at video game database company RAWG.io we’ve compiled ‘most abandoned’ and ‘most addictive’ reports for video games.

Do you make a popular service with valuable user behavior data? Funny data analysis reports are a good way to get some attention to your product. Take a lead from Pornhub, they are great at publicizing their data.

Link: https://www.gwern.net/GoodReads
Pornhub Insights: https://www.pornhub.com/insights/

—
This is a guest post by Samat Galimov, who writes about technology, programming and management in Russian on @ctodaily.


#DataAnalysis #GoodReads #statistics #greatstats #talkingnumbers

P-value, explained, one more time with demos

Article includes not only great explanation of what is #pvalue, but how it works and how it can be used to make a correct conclusions.

Link:https://www.freecodecamp.org/news/what-is-statistical-significance-p-value-defined-and-how-to-calculate-it/

#entrylevel #dsformanagers #tutorial #explained #interactive #statistics

Tail risk of contagious diseases

Fresh N. Taleb’s and Pasquale Cirillo’s article on risks of fat tail distribution.

Article: https://www.nature.com/articles/s41567-020-0921-x

#statistics #fattail

​​Overview of Open Source projects growth metrics

Quantative analytics of top starred repositories.

Link: https://medium.com/runacapital/open-source-growth-benchmarks-and-the-20-fastest-growing-oss-startups-d3556a669fe6

#opensource #analytics #statistics #growth

Benford’s Law, DS and the 2020 Election

This law can be used for the very basic check on wether the data was artificially generated or not. It assumes that lower digits have higher probability of occuring.

And there can be nothing better for #reproducibleresearch concept promotion, than #openresearch on poll data, because it shows that those can and should be transparent and open.

With the help of the repo below anyone can check compliance of poll data results with the #BenfordsLaw on unofficial (or official if you are able to get that data).

KDnuggets tutorial: https://www.kdnuggets.com/2020/09/diy-election-fraud-analysis-benfords-law.html
Github repo with examples on unofficial US election data: https://github.com/cjph8914/2020_benfords

#statistics

🔥Everything You Always Wanted To Know About GitHub (But Were Afraid To Ask)

ClickHouse team provided extensive statistics on GitHub, including but not limited to distribution of repositories by star count, top repositories by stars, affinity list, top labels etc.

All the data is available for download with instructions for ClickHouse import

Link: https://gh.clickhouse.tech/explorer/

#GitHub #ClickHouse #Yandex #statistics #EDA #engineerketing

🦜 Hi!

We are the first Telegram Data Science channel.

Channel was started as a collection of notable papers, news and releases shared for the members of Open Data Science (ODS) community. Through the years of just keeping the thing going we grew to an independent online Media supporting principles of Free and Open access to the information related to Data Science.


Ultimate Posts

* Where to start learning more about Data Science. https://github.com/open-data-science/ultimate_posts/tree/master/where_to_start
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Open Data Science

ODS.ai is an international community of people anyhow related to Data Science.

Website: https://ods.ai



Hashtags

Through the years we accumulated a big collection of materials, most of them accompanied by hashtags.

#deeplearning #DL — post about deep neural networks (> 1 layer)
#cv — posts related to Computer Vision. Pictures and videos
#nlp #nlu — Natural Language Processing and Natural Language Understanding. Texts and sequences
#audiolearning #speechrecognition — related to audio information processing
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#OpenAI #microsoft #Github #DeepMind #Yandex #Google #Facebook #huggingface — hashtags related to certain companies
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Chats

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ODS resources

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#cheatsheet #statistics