What learning material would you suggest for a CS person / novice statistician / novice mathematician to get into predictive analytics?

  • $\begingroup$ Possible duplicate: stats.stackexchange.com/questions/652/… $\endgroup$ – Shane Aug 22 '10 at 22:43
  • $\begingroup$ I collected some links here: meta.stats.stackexchange.com/questions/6/… $\endgroup$ – ars Aug 23 '10 at 4:47
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    $\begingroup$ This Q has reappeared on the 'active questions' page as it was 'poked' by the 'Community' background process, one of whose tasks is "Randomly poke old unanswered questions every hour so they get some attention". I don't think this question deserves any more attention. It's community wiki, it received only one up-vote, got a reasonable answer on Aug 26 but the user who asked it was last seen on Aug 24, so it seems unlikely that user is ever going to accept an answer. I suggest it should be closed by a moderator. $\endgroup$ – onestop Oct 26 '10 at 6:40

Further to my previous note - I'd just like to let people know that my new book: Predictive Analytics, Data Mining and Big Data. Myths, Misconceptions and Methods is now out. Available at amazon and all good book shops:


Eric - your book is recommended reading.

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    $\begingroup$ Please register & merge your 2 accounts (see here). Then you will be able to edit your previous posts, among other advantages. $\endgroup$ – gung - Reinstate Monica Sep 10 '14 at 20:38

Go to http://www.vaultanalytics.com/books

They have written a book on what predictive models are, when to use what tests/models, and how to create them in Excel. I'm using it every day in my job. I think it's extremely useful.

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    $\begingroup$ Critical errors in Excel are well described. See for example biostat.mc.vanderbilt.edu/ExcelProblems. It's difficult to see why Excel would be used when there are much better free resources around (e.g., R). $\endgroup$ – Frank Harrell Jul 7 '11 at 19:58

There are quite a few books around. The above are all pretty good. I've also done a book focusing specifically on predictive analytics in retailing and financial services.

Finlay, Steven (2012). Credit Scoring, Response Modeling and Insurance Rating. A Practical Guide to Forecasting Customer Behavior. Basingstoke: Palgrave Macmillan. ISBN 0-230-34776-2.

Its certainly not a "Hard core" mathematics book, but it does give a basic introduction to they key methods such as logistic regression, neural networks etc. In particular it focuses on the entire model development process. Starting with project planning and going through to implementation and monitoring of the model post live.


I wrote a book on this topic:

"Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die", by Eric Siegel, Ph.D. (Wiley, February 2013)

More info: http://www.thepredictionbook.com

The Fiscal Times ran an excerpt as an article: http://www.thefiscaltimes.com/Articles/2013/01/21/The-Real-Story-Behind-Obamas-Election-Victory.aspx

And there are other excerpts available throught the book website above.

Let me know if you have any questions about the book!

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    $\begingroup$ Eric, for some reason your site is very poorly rated with Web of Trust. Apparently for malware? mywot.com/en/scorecard/… $\endgroup$ – Dan Filimon Mar 4 '13 at 16:30

Reading this one now: Predictive Analytics: Microsoft Excel

By Conrad Carlberg

Published Jul 2, 2012 by Que.

  • ISBN-10: 0-7897-4941-6 ISBN-13: 978-0-7897-4941-3

I'm not done reading it yet, but so far its a good introduction to the topic for a non-stat person. It starts pretty basic with both stat concepts and Excel functionality and is building from there.

On the Stats front, its going into a pretty healthy discussion of of using moving averages and smoothing to help determine signal/noise in time series.

On the Excel front, its explaining how to build models using the above concepts (rather than just plunking a typical Excel trendline on a chart), and using some of Excels add-on functionality (e.g. Solver and Data Analysis).


There's no need to call it Predictive Analytics :) It already has two names: statistics, and data mining.

Beginner Stats Book: Statistics in Plain English
Advanced Stats Book: Multivariate Analysis, by Hair
Data Mining Book: I still haven't found a great one, but Data Mining by Witten is okay.

Don't get too confused by all the details. There are only so many things you can accomplish in general:

  1. predict a real number (regression)
  2. predict a whole number (classification)
  3. modeling (same as the above two, but the model is understandable by humans)
  4. group similar observations (clustering)
  5. group similar factors (factor analysis)
  6. describe a single factor
  7. describe the relationship between multiple factors (correlation, association, etc)
  8. determine if a population value is different from another, based on a sample
  9. design experiments and calculate sample size

good luck!

  • $\begingroup$ No specific thoughts on the Tibshirani, Hastie book, Elements of Statistical Learning? Very comprehensive overview of various methods. I think that would be a great advanced data mining book, anyway. $\endgroup$ – AdamO Jan 23 '13 at 6:39
  • $\begingroup$ "Beginner Stats Book: Statistics in Plain English" There are two different books with that same same title by different authors. Is the one referred to here by Harvey J. Brightman or Timothy C. Urda? $\endgroup$ – user19959 Jan 23 '13 at 6:53
  • $\begingroup$ Isn't it also Machine Learning? Also, see this question. $\endgroup$ – Dan Filimon Mar 4 '13 at 16:32
  • $\begingroup$ Predict a whole number is not classification but rather models like Poisson, NBD, etc. Please be careful with your terminology where it matters. $\endgroup$ – Ari B. Friedman Apr 23 '13 at 12:56

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