Other Resources

This website is only for introductory learning. For additional information on quantitative methods and learning other statistical packages, I recommend the following source material.  Comments in italics are my own.


YouTube Video Channels–just a few of the many out there.  Be sure to search for specific methods and models; you might be surprised at the results.


  • Quantitative Social Science: An Introduction by Kosuke Imai, Princeton Press, 1st edition (August 2017), ISBN: 9780691175461
    —I don’t have this book yet, but I’m pretty eager to check it out as a potential textbook for teaching an intro to stats class. It is written by a well-published political methodologist, designed to scale from undergrad to graduate courses, and uses R as the stats package for examples.
  • Statistics: A Tool for Social Research by Joseph F. Healey, Wadsworth Publishing, 8th edition (February 14, 2008), ISBN-10: 0495096555, ISBN-13: 978-0495096559
    —This was my graduate statistics textbook. Healey covered the foundation I needed and is a good book overall to have on hand.
  • Multiple Regression: A Primer by Paul D. Allison, Sage Publications, 1st edition (December 29, 1998), ISBN-10: 0761985336, ISBN-13: 978-0761985334
    —Allison is an authority on regression analysis and many other stats topics. This is a small, easy to read book that I’d say fills in the classroom gaps. It covers linear and multiple linear regression well. Too bad it did not continue with logistic regression.
  • Quantitative Applications in Social Science Series–numerous books by many authors–Sage Pulications, Link to publisher’s list.
    —These are very handy little books. Unfortunately, last I checked, the SAGE website does a poor job of making the full book list easily searchable. Each covers specific aspects, techniques, and statistical designs. Because of the topic and author variety, they vary in recommended background knowledge and writing style. Check your library first for these books.
  • Statistical Models for Social Researchers by Roger Tarling, Social Research Today, 1st edition (October 31, 2008), ISBN-10: 0415448409, ISBN-13: 978-0415448406
    —I highly recommend this book. It is a smooth read with easy to understand explanations. It has a good balance between formula and statistical package screenshots. Model fitting examples cover SPSS, STATA, and MLwiN. It is a one-stop shop book for most modeling needs.
  • Practical Statistics: A Quick and Easy Guide to IBM® SPSS®, STATA, and Other Statistical Software by David Kremelberg, SAGE Publications, 1st edition (March 10, 2010), ISBN-10: 1412974941, ISBN-13: 978-1412974943
    —This book offers great step-by-step procedures, screenshots, and output. Kremelberg provides insight on some of the model options, but falls short on a few common model features and output analysis. Still, great book overall for SPSS and STATA, particularly if you are moving between the packages.
  • Regression Models for Categorical and Limited Dependent Variables by J. Scott Long, SAGE Publications, 1st edition (January 9, 1997), ISBN-10: 0803973748, ISBN-13: 978-0803973749
    —This book is not entry-level. It is a treasure trove of theory and example for binary, ordinal, nominal, Tobit, and count data models. However, it does not cover any statistical package information. It is formula and math heavy, but provides a solid background for these models.
  • Regression Models for Categorical Dependent Variables Using STATA by J. Scott Long and Jeremy Freese, STATA Press, 2nd Edition (November 15, 2005), ISBN-10: 1597180114, ISBN-13: 978-1597180115
    —This book is the second edition to the one above, but has substantial changes from the first edition. It is less stats-math heavy and includes STATA how-to guides for all the model examples. For users unfamiliar with STATA, it provides an introductory, basics chapter. I feel it does not cover the depth of the first edition, but it much more accessible.
  • The STATA Survival Manual by David Pevalin and Karen Robson, Open University Press, 1st edition (July 1, 2009), ISBN-10: 0335223885, ISBN-13: 978-0335223886
    —When it comes to learning STATA, this book is the bootcamp you’ll need. If I was to teach introductory stats with STATA, this book would certainly be on the required list. It advances step-by-step with an abundance of screenshots, syntax, and output examples. It covers many of the topics I present on this website, but using STATA rather than SPSS. It does not cover advanced techniques and modelling, but should be more than enough to carry you into one of the boxes listed above.
  • Introductory Econometrics: A Modern Approach by Jeffrey Wooldridge, Cengage Learning, 6th edition (Oct 8, 2015), ISBN-10: 1305404211, ISBN-13: 9781305404212
    —Affectionately known as ‘Little Wooldridge’, this was my PhD applied econometrics textbook and written by one of the giants in economics instruction. It starts with a deep dive into the principles of regression and builds upon those foundations. While not always the most exciting stats book to read, it builds a comprehensive toolkit of advanced regression techniques. Computer examples are not software specific, and gives instructors supplemental materials for using several packages like R, Stata, and Minitab. Big or Papa Wooldridge is the even-more advanced version used in economics departments.
  • Statistics for People Who (Think They) Hate Statistics by Neil J. Salkind, Sage Publications, 6th edition (Sept 27, 216), ISBN-10: 1506333834, ISBN-13: 978-1506333830—My comments reflect having the 2nd edition. It was a fun read, designed more like a ‘For Dummies’ book. It starts with the basics and carries up to Chi-Square and some non-parametric analysis. It touches only briefly on regression and other more advanced techniques. It is good for those that might struggle a bit at the beginning of a stats class and always good to keep handy for rethinking how to explain intro stats, but you’ll quickly move onto more advanced texts. The examples use SPSS.

Other useful items