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Old 06-15-2018, 11:26 AM   #1
pkratitsbest
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Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

Recently, I just imported PT4 database into SPSS and ran some correlational analysis. It seems fun. Basically in many spots, we have a tiny sample of a specific action (e.g. bet flop then c/f turn). But we may have a very large sample of other stats (e.g. WTSD, PFR, etc). We can check if Specific Small Sample Stat A is correlated with General Large Sample Stat B. If A is positively correlated with B, we can use B to infer and guesstimate A.

Anyone also use SPSS/Python/Matlab or whatever programs to do this sort of stuffs?

I am very new to programming. Apart from correlational analysis, what analysis can be ran (which is useful for poker)? What programs are best for doing this sort of work?

Last edited by pkratitsbest; 06-15-2018 at 11:32 AM.
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Old 06-16-2018, 04:02 PM   #2
roundhouse
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

Not quite tried that. But I might at some point. I've been using Python recently to do a bit poker-economy simulation for interest / programming practice. I'd recommend Python or R for the sort of statistical analysis you're after. For Python, use Anaconda (Google it) and Jupyter Notebooks. For R, use RStudio. Check out Datacamp.com for training on both.
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Old 06-16-2018, 07:14 PM   #3
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

I've used R and Python/numpy a bit for various academic research. I'd go with Python just because you're learning a real-life programming language that's useful for a lot more than just high-powered stats. R feels like it was written by academics, which is was, so its funky syntax tilts me. I did discover one really useful R function that wasn't present in a Python library, I forget which, but in general Python is fun and intuitive.

(R is valuable in the job market because it's mostly data science folks using it; Python is valuable because it's far far far more common in industry jobs.)

+1 for Anaconda -- comes with numpy, scipy, pandas, all libraries you'll want to be using. The Jupyter Notebook is nice for sharing quick and dirty calculations in a systematic format.

For serious debugging, I highly recommend PyCharm (which is free for students).
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Old 06-16-2018, 07:24 PM   #4
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

R syntax confirmed horrible
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Old 06-17-2018, 09:56 PM   #5
pkratitsbest
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

Quote:
Originally Posted by AKQJ10 View Post
I've used R and Python/numpy a bit for various academic research. I'd go with Python just because you're learning a real-life programming language that's useful for a lot more than just high-powered stats. R feels like it was written by academics, which is was, so its funky syntax tilts me. I did discover one really useful R function that wasn't present in a Python library, I forget which, but in general Python is fun and intuitive.

(R is valuable in the job market because it's mostly data science folks using it; Python is valuable because it's far far far more common in industry jobs.)

+1 for Anaconda -- comes with numpy, scipy, pandas, all libraries you'll want to be using. The Jupyter Notebook is nice for sharing quick and dirty calculations in a systematic format.

For serious debugging, I highly recommend PyCharm (which is free for students).
Thanks a lot for the advices!

What kind of academic research?

I may do poker research in the future, from judgement and decision making perspective, psych-oriented but may tough a bit on behavioral economics (not the hardcore maths stuffs tho). Maybe sth related to risk but I'm not sure yet.
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Old 08-14-2018, 09:49 AM   #6
moon_maiden207
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

Both R and MATLAB toolboxes provide great options for neuronal networking, psychophysics/behavioural analytics research and genomic and bioinformatics work.

If you would like to pursue decision making research with a focus on computational neuroscience/psychology R is perfect for such analysis. Use stack overflow, GitHub for information hacking.

If you would like to design experimental paradigm MATLAB (psych toolbox) and
PsychoPy are initial platforms to use.

Of course PsychoPy and R are open source with great developer communities so I personally prefer using them over MATLAB. However in academic research (I work on cognitive neuroscience) avoiding MATLAB completely is not possible.
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Old 08-14-2018, 09:51 AM   #7
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

ps: I have used SPSS extensively and would suggest using R over SPSS any day.
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Old 08-16-2018, 10:30 AM   #8
jdr0317
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

I actually like R with regards to these kind of exploratory analyses. Scikit-learn in Python, for example, is much more about "create model, save model for future" than for generating insight into the data (and I hate the statsmodels package.

It'd be fun to take standard spots leading up to a street and try to calculate the exploitative optimal play against generic (and specific) opponents for sure. Obviously when I say generic exploit, I mean like "how does the average NL2 guy play?"
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Old 08-16-2018, 03:16 PM   #9
moon_maiden207
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Re: Anyone use SPSS/Python/Matlab or whatever programs to do data analysis?

Quote:
Originally Posted by jdr0317 View Post
I actually like R with regards to these kind of exploratory analyses. Scikit-learn in Python, for example, is much more about "create model, save model for future" than for generating insight into the data (and I hate the statsmodels package.

It'd be fun to take standard spots leading up to a street and try to calculate the exploitative optimal play against generic (and specific) opponents for sure. Obviously when I say generic exploit, I mean like "how does the average NL2 guy play?"
How does one define generic play as in the play by the 'average NL2 guy'? Unless one does a ton of data mining to define the generic model? Also may be calculate exploitative optimal play between specific opponent and one that plays the mathematically optimal game (obv. the latter is a hypothetical)? calculating how much a specific player deviates from optimal play (rather than the average NL2 play) might give more stable information.
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