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Teaching Statistics Using Baseball | 
 enlarge | Author: Jim Albert
Publisher: The Mathematical Association of America
Category: Book
List Price: $56.95
Buy New: $36.26
You Save: $20.69 (36%)
New (3) Used (12) from $35.21
Rating:  3 reviews
Sales Rank: 460690
Media: Paperback
Number Of Items: 1
Pages: 304
Shipping Weight (lbs): 1.2
Dimensions (in): 9.7 x 7 x 0.7
ISBN: 0883857278
Dewey Decimal Number: 519.5
EAN: 9780883857274
ASIN: 0883857278
Publication Date: July 2003
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
Condition: Book is brand new, and has never been opened. Thousands of satisfied customers!
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| Editorial Reviews:
Product Description
"Teaching Statistics Using Baseball " is a collection of case studies and exercises applying statistical and probabilistic thinking to the game of baseball. Baseball is the most statistical of all sports, since players are identified and evaluated by their corresponding hitting and pitching statistics. There is an active effort by people in the baseball community to learn more about baseball performance and strategy by the use of statistics. This book illustrates basic methods of data analysis and probability models by means of baseball statistics collected on players and teams. Students often have difficulty learning statistics ideas since they are explained using examples that are foreign to the students. The idea of the book is to describe statistical thinking in a context (that is, baseball) that will be familiar and interesting to students. The book is organized using a same structure as most introductory statistics texts. There are chapters on the analysis on a single batch of data, followed with chapters on comparing batches of data and relationships. There are chapters on probability models and on statistical inference. The book can be used as the framework for a one-semester introductory statistics class focused on baseball or sports. This type of class has been taught at Bowling Green State University. It may be very suitable for a statistics class for students with sports-related majors, such as sports management or sports medicine. Alternately, the book can be used as a resource for instructors who wish to infuse their present course in probability or statistics with applications from baseball.
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| Customer Reviews:
statistics professor teaches statistics and sabermetrics April 18, 2008
42 out of 42 found this review helpful
Jim Albert is a Professor of Statistics at Bowling Green University. He is an excellent teacher and researcher. He has written a number of fine statistics books including a recent one on doing Bayesian statistics using R. He is also an avid baseball fan and has published statistical articles and books on the subject. My favorite is "Curve Ball" which he coauthored with Jay Bennett. He is one of the leaders in the American Statistical Associations section on statistics in sports.
Once at an ASA meeting I heard him give a talk about how he was able to make statistics exciting for non-statistics majors by teaching it solely using baseball examples. His course became one of the most popular in the school which is amazing. Most students who are required to take statistics don't understand why it is an important discipline to learn about. They are usually bored to tears because of the dry presentation of the usual statistics lectures. These courses are generally hated by these students and they avoid them if at all possible. Albert's approach is new and seems to be working. I think he wrote this book for statistics teachers to help them learn how to teach a course like this. This book can serve as a basic statistics text or as a reference for those fond of sabermetrics.
an excellent read, very helpful August 9, 2003
11 out of 11 found this review helpful
What a great way to learn some of the basics of statistics. This book is meant to cover most of the material that a standard statistics textbook would, but using solely examples from the game of baseball. I picked it up primarily for the sections on probability, but have enjoyed the entire thing so far. Obviously a lot of work went into its preparation, and one of the most impressive aspects is the sheer number of exercises at the end of each chapter -- more than enough to reinforce the central points.
A hit about hits August 7, 2003
29 out of 29 found this review helpful
If there is one thing that separates the baseball fan from those of other sports, it is their fascination with statistics. By this, I mean the raw data, not the detailed analysis. An enormous amount of data is kept about baseball players and their accomplishments, and nearly all of it is online. It is very detailed, as it is possible to obtain data regarding how a particular batter performed when facing a particular pitcher with a particular ball and strike count. With all of this data available, it is possible to find some raw data that can be used to illustrate any analytical technique demonstrated in basic statistic classes.
Using this data, the authors have hit a resounding home run, and touched all the bases. The examples are easily understood, even if you have limited knowledge of the game. Nearly all of the techniques of a basic statistics class are covered, making this suitable for use as a textbook. The main points of difference are the absence of a great deal of hypothesis testing and the inclusion of a chapter on the events of an inning modeled as a Markov chain.
Baseball fans will want to read this book to settle arguments and start new ones. One can argue, as I have on many occasions, about which of two players is the best or which one should have been the Most Valuable Player (MVP) for a particular year. There are some very detailed comparisons of players, showing conclusively, at least to me, which one was best. I was fascinated about the run producing value of all of the possible offensive outcomes of a batter getting on base by getting a hit, walk or being hit by a pitch. Their analysis includes the value of advancing runners already on base, which explains why a single is worth 1.0 and a walk worth 0.61. Runners often advance more than one base on a single and a walk will advance runners only if first base is already occupied. A large collection of problems is given at the end of each chapter and the data for the problem is always included.
At this point in my professional life, I dread the examination of textbooks for basic classes. Over time, they seem to take on a bland sameness that dulls the mind, even though they do have differences. This is the liveliest, most interesting statistics book that I have ever read.
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