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All of Statistics, by Larry Wassserman (2013) [pdf]

stat.cmu.edu

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Re: All of Statistics, by Larry Wassserman (2013) [pdf]

#51

Post by kgwgk »

pddpro wrote: post #41

How does this compare to, say "Introduction to Statistical Learning" and "Elements of Statistical Learning" by Trevor et al? As I understand, the former is also supposed to be a concise introduction to statistical concepts while the latter offers a more rigorous treatment. Where does this book fall in between?

This book is not between ISL and ESL. All of Statistics is an introductory course (and has a much wider scope, including advanced topics) while even the watered-down ISL assumes that the reader knows already a bit of statistics.

Re: All of Statistics, by Larry Wassserman (2013) [pdf]

#52

Post by jeffwass »

MichailP wrote: post #20
jeffwass wrote: post #14

Earlier quoted context omitted.

As an EE, how would you explain concepts like a PN junction or field effect transistor without using statistical mechanics? (Ie, expected behaviour for ensembles of huge numbers of particles).

The models EE use are simplified, drift and diffusion current and electron and holes with their different mobilities and energy levels. Math apparatus used here, and strictly related to statistics, is limited to averaging, I would dare to say.

Great. Those formulae are derived from statistical representation of huge number of particles, eg electrons modelled as a nearly-free gas of fermions obeying Fermi-Dirac statistics. And so too would anything making use of PN junctions, band gaps, especially when considering temperature dependence.

I think you can agree now that your original observation of statistics as "glorified curve fitting" as a bit naive.

Re: All of Statistics, by Larry Wassserman (2013) [pdf]

#53

Post by mathheaven »

stdbrouw wrote: post #50

While All of Statistics is wonderful in its genre, it really isn't a good place to start to learn statistics. Firstly because it focuses very heavily on the theory and contains very little on practical modeling. Secondly because the theory isn't even necessarily going to be very enlightening: frequentist statistics is a mathematical tour de force, using every possible hack you can think of to be able to draw statisti…

Brian Blais's free book doesn't contain any reference to the Poisson Distribution.

For ML Hastie and Tibshirani ISLR is very good but is more for applications of machine learning: classification, regression and prediction.

Re: All of Statistics, by Larry Wassserman (2013) [pdf]

#54

Post by stdbrouw »

mathheaven wrote: post #53
stdbrouw wrote: post #50

While All of Statistics is wonderful in its genre, it really isn't a good place to start to learn statistics. Firstly because it focuses very heavily on the theory and contains very little on practical modeling. Secondly because the theory isn't even necessarily going to be very enlightening: frequentist statistics is a mathematical tour de force, using every possible hack you can think of to be able to draw statisti…

Brian Blais's free book doesn't contain any reference to the Poisson Distribution. For ML Hastie and Tibshirani ISLR is very good but is more for applications of machine learning: classification, regression and prediction.

The Poisson distribution is just a limiting case of the binomial distribution and not needed to explain any of the concepts that drive statistical inference, so its absence from an introductory text is hardly something to fuss about.
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