Buy New
$15.04
Qty:1
  • List Price: $19.00
  • Save: $3.96 (21%)
FREE Shipping on orders over $35.
Only 18 left in stock (more on the way).
Ships from and sold by Amazon.com.
Gift-wrap available.
Add to Cart
Trade in your item
Get a $5.27
Gift Card.
Have one to sell? Sell on Amazon
Flip to back Flip to front
Listen Playing... Paused   You're listening to a sample of the Audible audio edition.
Learn more
See this image

A Mathematical Primer for Social Statistics (Quantitative Applications in the Social Sciences) Paperback – July 29, 2008

ISBN-13: 978-1412960809 ISBN-10: 1412960800 Edition: 1st

Buy New
Price: $15.04
33 New from $15.04 10 Used from $16.98
Rent from Amazon Price New from Used from
eTextbook
"Please retry"
$4.84
Paperback
"Please retry"
$15.04
$15.04 $16.98

Free%20Two-Day%20Shipping%20for%20College%20Students%20with%20Amazon%20Student




Frequently Bought Together

A Mathematical Primer for Social Statistics (Quantitative Applications in the Social Sciences) + Basic Math for Social Scientists: Concepts (Quantitative Applications in the Social Sciences) + Basic Math for Social Scientists: Problems and Solutions (Quantitative Applications in the Social Sciences)
Price for all three: $48.12

Buy the selected items together

If you buy a new print edition of this book (or purchased one in the past), you can buy the Kindle edition for only $2.99 (Save 70%). Print edition purchase must be sold by Amazon. Learn more.

Save up to 90% on Textbooks
Rent textbooks, buy textbooks, or get up to 80% back when you sell us your books. Shop Now

Product Details

  • Series: Quantitative Applications in the Social Sciences (Book 159)
  • Paperback: 184 pages
  • Publisher: SAGE Publications, Inc; 1 edition (July 29, 2008)
  • Language: English
  • ISBN-10: 1412960800
  • ISBN-13: 978-1412960809
  • Product Dimensions: 0.4 x 5.5 x 8.5 inches
  • Shipping Weight: 8 ounces (View shipping rates and policies)
  • Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
  • Amazon Best Sellers Rank: #88,016 in Books (See Top 100 in Books)

Editorial Reviews

About the Author

John Fox is the Senator William McMaster Professor of Social Statistics in the Sociology Department of McMaster University in Hamilton, Ontario, Canada. Professor Fox earned a Ph.D. in sociology from the University of Michigan in 1972. He has delivered numerous lectures and workshops on statistical topics, at such places as the summer program of the Inter-University Consortium for Political and Social Research, the annual meetings of the American Sociological Association, and the Oxford Spring School in Quantitative Methods for Social Research. He has written many articles on statistics, sociology, and social psychology, and is the author of several books on statistics, including most recently Applied Regression Analysis and Generalized Linear Models, Second Edition (Sage, 2008) and A Mathematical Primer for Social Statistics (Sage, 2009), and (with Sanford Weisberg) An R Companion to Applied Regression, Second Edition (Sage, 2011). Professor Fox is an active contributor to the R Project for Statistical Computing and is a member of the R Foundation. His work on this book was partly supported by a grant from the Social Sciences and Humanities Research Council of Canada..

More About the Author

Discover books, learn about writers, read author blogs, and more.

Customer Reviews

5.0 out of 5 stars
5 star
1
4 star
0
3 star
0
2 star
0
1 star
0
See the customer review
Share your thoughts with other customers

Most Helpful Customer Reviews

9 of 9 people found the following review helpful By Timothy P. Foley on July 31, 2010
Format: Paperback Verified Purchase
This gem of a book provides a concise and quite readable overview of important mathematical concepts that are important for understanding both basic and advanced statistical methods, not only for sociologists, but any practitioner of applied statistics. John Fox has successfully pulled together and integrated into a 166 page primer mathematical concepts that often appear scattered in more advanced mathematics courses, including advanced calculus courses that many users of applied statistical methods might not have taken. The book starts with an introduction and overview of matrices, linear algebra, and vector geometry. The material in this chapter is absolutely essential to anyone who wishes to use multivariate methods such as principle components analysis and should be mastered even if the reader chooses not to finish the book. The following chapter provides an astonishingly practical review of differential and intgeral calculus concepts important to statistics; after a brief review of planes, functions, and limits of functions, Dr. Fox quickly reviews differentiation of functions,optimization problems involving derivatives, multivariate and matrix differential calculus, Taylor's theorem, and finally an overview of integral calculus whose concepts are important in understanding probability distributions. Chapter 3 provides an excellent introduction to mathematical statistics to include properties of various distributions and estimators, maximum-likelihood estimation, and an introduction to Bayesian inference. Chapter 4 entitled "Putting the Math to Work: Linear Least Squares Regression" closes out this primer and shows how the method of least squares and the Gauss-Markov Theorem is used to estimate regression parameters and associated statistics.Read more ›
Comment Was this review helpful to you? Yes No Sending feedback...
Thank you for your feedback. If this review is inappropriate, please let us know.
Sorry, we failed to record your vote. Please try again

Customer Images

Search