Data Analysis: An Introduction

By Michael S. Lewis-Beck

Book Overview

Written at a level appropriate for the advanced undergraduate course on data analysis, this accessible volume introduces the reader to the "art" of data analysis from data-gathering to multiple regression in which a dependent variable is influenced by several independent variables. The book focuses on the interpretation of a statistical result, in particular those that come from non-experimental social research. Using a consistent data set throughout the book in order to illustrate the various analytic techniques, the author covers such topics as univariate statistics, measures of association, the statistical significance of the relationship between two variables, and simple regression where the dependent variable is influenced by a single independent variable. The last chapter offers analysis recommendations. Data Analysis will provide social science researchers with the tools to select and evaluate statistical tests appropriate for their particular research question.

• Format: Paperback
• Language: English
• ISBN: 0803957726
• ISBN13: 9780803957725
• Release Date: January 1995
• Publisher: Sage Publications, Inc
• Length: 88 Pages
• Weight: 0.28 lbs.
• Dimensions: 0.2" x 5.5" x 8.3"

Customer Reviews

Quick & Easy Guide to Statistics

As a Phd student in sociology, I find this booklet indispensable as a quick and easy reference guide to all the basics of social science statistical analysis. After going through more complicated texts such as Lewis-Beck's "Applied Regression: an Introduction" and Berry and Feldman's "Multiple Regression in Practice", I find this small booklet extremely helpful and clear in its explanations of the logic of basic bivariate and multiple regression analysis, as well as significance testing. It is quite useful as a tool to review the basic methods of analysis, and I especially like the list of regression assumptions at the end, all of which we had to memorize and explain for qualifying exams! I would only request a separate section and more detailed explanation of the Chi-square test, complete with application examples.