Book Review

Data Happy! Doing Sociology with Student CHIP
Gregg Lee Carter
Boston: Allyn and Bacon
352pp.

Within the last decade, professors teaching introductory sociology courses have had their book selection choices vastly expanded. There is a wide variety of traditional textbooks, short of core introductory texts, and "invitation" type texts: with the advance of user-friendly computer technology there has been a related trend in the appearance of workbooks using the computer. This trend, far from being obscure, actually helps bring together what is crucial to sociology – "an appreciation of how data and theory fit together."

Carter’s workbook, Data Happy! Doing Sociology with Student CHIP accomplishes this goal. It is not the first nor will it be the last in the trend incorporating computers into teaching sociology, but it appears to improve upon its predecessors in at least three ways: (1) it provides a primer for critiquing sociological writing (both classic and contemporary); (2) it provides a primer on elementary data analysis and its connection to the problem of establishing causality; and (3) it employs a much broader range of data sources (the GSS, international censuses and vital statistics reports, FBI crime summaries, Gamson’s The Strategy of Social Protest, the 1968 Kerner Commission’s 15-city study, and historical materials from the former Lemberg Center for the Study of Social Violence at Brandeis University).

Computer exercises are organized around the major subfields of sociology and each set of exercises is introduced by a brief summary of some of the major concerns of that particular subfield with accompanying concepts and terminology. The workbook can stand alone, but I have used it with Carter’s book of readings, Empirical Approaches to Sociology: Classical and Contemporary Readings (1994), which parallels the assignments in Data Happy! The classical and contemporary readings in Empirical Approaches are preceded by a theoretical overview. This is basically the same structure as the workbook, although Data Happy! summarizes the readings.

There are three critical sections preceding the 11 chapters of this workbook. These sections present: (1) information on using the software and data sets included with the workbook; (2) a "primer on critical reading"; (3) a "primer of elementary data analysis. The instructions in the first section on using the software program are only slightly over five pages. These are succinct, thorough, and can be mastered easily by introductory-level students. The remaining part of section one describes the data sets.

Although I only require Data Happy! in my introductory courses. I use sections two and three in all courses. Section Two is a "must" for gaining intellectual insight in critiquing writing based on research. Section Three presents elementary concepts of data analysis such as measures of central tendency and dispersion, basic tabular analyses, scatterplots and the correlation coefficient, and the criteria for establishing causality.

Each of the 11 chapters is self-contained and need not automatically precede or follow another. They parallel topics contained in traditional textbooks: (1) The Problem of Social Order; (2) Issues in Sociological Research; (3) Culture; (4) Society; (5) Socialization; (6) Groups; (7) Interaction; (8) Crime, Deviance, and Social Control; (9) Inequality; (10) Race and Ethnicity; and (11) Gender. The exercises in each chapter begin with basic cross-tabulations followed by questions that guide the student through analysis and sociological inquiry. Next, advanced exercises are presented that include partial tables and control variables. Ideas of spuriousness, multivariate effects, interaction between variables, and time association are also introduced. Exercises examine intrinsically interesting questions. Examples include: Who’s most likely to stray from marital vows? Who’s most afraid to walk at night? What are the social characteristics of happy people? Who’s at risk for becoming homeless? Should we leave running the country up to men? An instructor’s manual is also available, which I have found to be invaluable.

I teach introductory students who have had very little, if any, experience in thinking quantitatively. I spend more time, therefore, on Sections Two and Three than other professors may find necessary. Although these sections are written clearly, I proceed slowly and give many supplementary elementary data analyses handouts before going to Chapter 1. In addition, I am mot able to move beyond basic tabular analyses or a brief introduction of control variables in my introductory course. I am hindered, not by Carter’s workbook, but by incoming students’ lack of preparation.

For those environmentally minded sociologists, Data Happy! is printed on recycled, acid-free paper!

Diane Balduzy, Teaching Sociology


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