PS: It is updated at 8/25/2020

PS2: It is updated again at 9/10/2020

Hi, there :d I am a senior student studying Industrial Engineering at Boğaziçi University. I am very interested in machine learning and deep learning topics so that I completed courses like Data Mining and Graph Theory. I did multiple internships on data science fields like machine learning and optimization. I am going to be full time Data Scientist or ML Engineer.

Statistical Models for Sport in R

This is of course about constructing statistical predictive models in sports area. In this field the well known, popular tasks are about to predict future winners. I found this interesting because in statistics course (IE256-Baydogan) one of our homework assignment was about football betting. We only used multiple linear regression to predict the winner since it was an introductory course.

By the way, did you know that the Pythagorean theorem is quite powerful to predict win expectations? I didn’t know too. It is actually great to prove that complex models aren’t always better, solving the problem easily as much as possible is much better.

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useR! 2020: rtables (G. Becker), regular

This is about a pretty new package. It’s still under development and it’s quite interesting that these studies are fully funded by Roche, the medicine firm. I found it interesting because I had a chance to meet people from Roche and I didn’t expect open-sourced contributions from firms like Roche :)

The mission of this package is related to a quite fundemental thing of analyses and visualizations in R. It makes tables more easily readable and functional by splitting rows, splitting columns, disposition tables etc. I think tables may be more useful than graphs time to time when structuring a complicated raw data into an easily readable and stylish tables is possible.

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Display your favorite XKCD comic in R

R isn’t just a statistics tool. It also promises fun. Yes, fun :) One can fetch a XKCD comic strip (randomly or by number) and displays it on screen. The serious thing about this is presentations may be more creative, catchy and fluent with these kind of tools right.

See an example below under “applied math” tag :)

Now an example below under “linear regression” tag :):)

Box plots?

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