Name: Introductory Statistics with R
ISBN: 9780387790541

Introductory Statistics with R

R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. R is now in widespread use for teaching at many levels as well as for practical data analysis and methodological development. This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. A supplementary R package can be downloaded and contains the data sets. The statistical methodology includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one- and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last six chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, survival analysis, Poisson regression, and nonlinear regression. In the second edition, the text and code have been updated to R version 2.6.2. The last two methodological chapters are new, as is a chapter on advanced data handling. The introductory chapter has been extended and reorganized as two chapters. Exercises have been revised and answers are now provided in an Appendix.

What Hacker News says

phillc73Mar 2021

Pete Dalgaard's Introductory Statistics with R is a good book, but not free online as far as I know.[1]

Or go to the source with An Introduction to R[2][3]

I also enjoyed Norm Matloff's fasteR tutorial.[4]

[1] https://www.springer.com/gp/book/9780387790534

[2] https://cran.r-project.org/doc/manuals/r-release/R-intro.pdf

[3] https://intro2r.com/the-aim-of-this-book.html

[4] https://github.com/matloff/fasteR

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gedrapDec 2016

- Introductory Statistics with R by Dalgaard, Peter. A solid introduction to stats, don't be scared by R bit in the title - it contains plenty of maths/theory so that knowledge is widely applicable. Brilliant introductory for everyone who wants to do something stats related. It's amazing how much can be done with no fancy deep learning algorithms, just plain simple stats.

- Statistics Done Wrong by Alex Reinhart. Plenty of gotchas with real world examples from academia. Well written and easy to read.

- The Circle by Dave Eggers. This one was scary. About imaginary corporation (a blend of Facebook and Google and Amazon) and probably not too distant future. If you liked Black Mirrors, you will love this.

- Brave New World by Huxley, Aldous. Classic novel with interesting thoughts about engineered society, where every human is assigned class, purpose in the society and feature at birth.

- Hatching Twitter: A True Story of Money, Power, Friendship, and Betrayal by Bilton, Nick. Read this book in a weekend, really well written and well researched about the inception of Twitter.

- Superforecasting: The Art and Science of Prediction by Tetlock, Philip E. A study on people with above average ability to forecast feature events (mostly geo-political). Talks about measuring predictions and improving them.

- The Black Swan by Nassim Nicholas Taleb. Brilliant book about overlooking rare events which have dramatic consequences because 'it's unlikely to happen'.

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stevenbedrickFeb 2011

I always seem to come back to "Introductory Statistics With R".[1] It gives a lot of examples of how to do "the day-to-day stuff". Also, since, as the title suggests, the statistical contents are mostly (very) introductory in nature, it's really easy for me as a reader to decipher what's going on in each example- it's easy to tell which parts are specific to the example itself and which parts are generic to R, if that makes any sense.

[1] http://www.powells.com/biblio/65-9780387790534-0

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rdoubleAug 2009

I was in the same boat as you. I have an undergrad math degree but took no statistics. I have found that most statistics books are inscrutable at best and complete wastes of paper and effort at worst. Based on the book recommendations I've been given by people who supposedly use statistics all the time, I don't believe that many trained statisticians have any idea what they are doing.

That said, here's what has sort of worked for me:

- Cartoon Guide to Statistics by Larry Gonick

- Fundamentals of Applied Probability Theory by Al Drake: out of print, and mostly about probability. However, the stats intro at the end is the clearest one I've ever read. Originally recommended to me by Philip Greenspun.

- Introductory Statistics with R by Peter Dalgaard. I'm assuming if you are posting to Hacker News you probably are coming from a programming background. This book does exactly what the title says, shows you how to apply introductory statistics by programming. It's heavier on R than stats.

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cholanteshDec 2016

>- Introductory Statistics with R by Dalgaard, Peter.

If one is new to R, would this text be a good intro to the language?

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kqr2Jan 2010

Zed actually recommends quite a few books in his post:

    * Statistics; by Freedman, Pisani, Purves, and Adhikari. Norton publishers.
    * Introductory Statistics with R; by Dalgaard. Springer publishers.
    * Statistical Computing: An Introduction to Data Analysis using S-Plus; by Crawley. Wiley publishers.
    * Statistical Process Control; by Grant, Leavenworth. McGraw-Hill publishers.
    * Statistical Methods for the Social Sciences; by Agresti, Finlay. Prentice-Hall publishers.
    * Methods of Social Research; by Baily. Free Press publishers.
    * Modern Applied Statistics with S-PLUS; by Venables, Ripley. Springer publishers.

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