This week Books by the Numbers takes a break from the "Fast Forward" entries to return to the subject of study, the 000s. However, we are remaining in the guest author mode! This week's guest post is submitted by Emmetsburg Public Library's own--actually, we share her with Iowa Lakes Community College--Mary Faber.
Mary Faber is TRIO Director at Iowa Lakes Community College, where she oversees three federally funded programs for students in grades 6th - 12th, as well as first and second year transfer students at the community college. Mary obtained a baccalaureate degree in social work/management from the University of Northern Iowa, a master's degree in Education from the University of Iowa, and is currently in the final stages of completing her quantitative dissertation (with a qualitative insert) at Iowa State University. Her working title, 'Gender Differences in Community College Transfer Students to a Midwestern Land Grant University' is challenging her to relate her quantitative data in the most understandable of ways.
You will see that Mary's apple is not falling far from the tree in her choice of books to write about for the blog, for she has chosen a modern day classic of research and statistical methods. She is featuring the venerable and scholarly--yet accessible--The Visual Display of Quantitative Information, by Edward R. Tufte, 2nd ed (001.4 TU).
Take it away Mary...
In the pursuit of a PhD, I have found myself drawn to books and publications that are often asking me to think differently or grow intellectually. One such example is The Visual Display of Quantitative Information by Edward R. Tufte.
The book begins with a bulleted list defining quantitative data; with that the author also reveals his reverence for this subject. The first two chapters are spent discussing the history of quantitative data and how its interpretation has largely been by placing dots on a grid. It also highlights the shortcomings of such measurements, as each graph looks like the last graph, and each line drawn in succession measures a different set of data, yet looks eerily similar. The overall premise of the book emerges early, and gives examples of how statistical, quantitative data can become some of the strongest communication tools available to us, if we can broaden how the data is represented.
From there, the author gives us numerous examples of how transferring statistical data to a variety of visual concepts can illuminate the data, and allow a greater understanding in a visual way. The book continues to encourage us to illustrate quantitative data and make it more user friendly and understandable. Interestingly enough, the author is convincing in proposing this transition, and I found myself challenged to convert everyday statistics to such examples.
This book certainly has applications for someone who is involved in research. But the surprisingly interesting twist is that even the casual reader might find this concept appealing. Part of the charm of this book is the difficulty with which it is written; it is a not a Sunday afternoon read. However, I would recommend this book for anyone who has a sense of curiosity about the world. You might just find yourself looking at things in a different light. This book challenged my thinking, and that’s a good thing.
