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Honestly, the only way to understand regression is to study Nike Hoodie Womens

something like Mccullagh Nelders book. Anything else and you are going to have a very hard time really being useful without misinterpreting the results.

Nike Jacket Women White

Nike Jacket Women White

Nike Jacket Women White

kayge 630 days ago linkmagicarp 630 days ago link

After that you can take the AI course on Udacity.

I'm taking this right now. Can somebody provide some perspective on how thoroughly the course prepares you for using R? Does it give you a good enough grounding in statistics so that you won't shoot yourself in the foot with R?

BasilAwad 630 days ago link

Nike Jacket Women White

Nike Jacket Women White

Nike Jacket Women White

How about not beginners looking to refresh / deepen their intuitions?I've recently been working with the Python toolset in this space pandas, numpy, matplotlib and run Nike Tracksuit Black And Red

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ikram 630 days ago linkchernevik 630 days ago link

smack dab into my rusty regression analysis. For straight up linear regression, with a heavy emphasis on observational data appropriate for microeconometrics, "Introductory Econometrics: A Modern Approach" by Jeff Wooldridge is absolutely phenomenal (an old edition is fine). I don't Nike Tracksuit Online

gwern 630 days ago Nike Jacket Women White linkpathy 629 days ago link

Nike Jacket Women White

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Thanks for the link, I have been meaning to revise some statistics, four years of barely doing any makes you forget a lot.

know Cleveland's books would help with the issues you asked about, but. It's the only economics text I'm keeping from university I'm getting rid of all the rest. It really digs into the material and highlights the pitfalls and incorrect assumptions in regression and forecasting. I'm planning to consult it when I start working on analytics in current/future projects.

You really aren't going get much out of it without working on some interesting data/stats problems. Though, many of the functions that R provides just won't make any sense at all if you don't have an intuition for the statistics behind it. Yes there are many "truths" in 'stats 101' that can be questioned, but this is the common language you'll want talking to any of these people."What is a p value anyway?" A very quick, non math heavy read on avoiding magical thinking in classical statistics."Data Analysis with Open Source Tools" I really love this book because it steps way out of "stats 101" land and gives a lot of really great real world advice and touches on many mathematical tools that can help you understand data. The chapter "What you really need to know about classical statistics" gives a refreshing overview of all the basic stats you've covered and explains many things that seem strange. Obviously learn the advanced statistics relevant to your interests, but when you get a chance listen to how other people think about stats, and keep learning.

A new online course

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