Making sense of statistical methods in social research

Select an Action

Title:

Making sense of statistical methods in social research

Author:

Yang, Keming, 1965-

ISBN:

9781847872869

9781847872876

Personal Author:

Yang, Keming, 1965-

Publication Information:

Los Angeles ; London : SAGE, 2010.

Physical Description:

xiii, 198 p. : ill. ; 25 cm.

Contents:

Introduction -- The use of statistical methods in social research -- Cases and variables -- The logic of sampling -- Estimating and measuring one important thing -- Studying the relationship between two variables -- Linear regression models and their generalizations -- Time matters -- Statistical case-oriented methods -- Methods for analysing latent variables -- Causal analysis.

Subject Term:

Social sciences -- Research -- Statistical methods.

Copies:

Available:*

Library	Material Type	Item Barcode	Shelf Number	Copy	Status
Searching... 1:IIEMSA	1:GEN-BOOK	33168025504867	300.727 Y22M 2010	1	Searching... Unknown

Bound With These Titles

On Order

Summary

Making Sense of Statistical Methods in Social Research is a critical introduction to the use of statistical methods in social research. It provides a unique approach to statistics that concentrates on helping social researchers think about the conceptual basis for the statistical methods they′re using.

Whereas other statistical methods books instruct students in how to get through the statistics-based elements of their chosen course with as little mathematical knowledge as possible, this book aims to improve students′ statistical literacy, with the ultimate goal of turning them into competent researchers.

Making Sense of Statistical Methods in Social Research contains careful discussion of the conceptual foundation of statistical methods, specifying what questions they can, or cannot, answer. The logic of each statistical method or procedure is explained, drawing on the historical development of the method, existing publications that apply the method, and methodological discussions. Statistical techniques and procedures are presented not for the purpose of showing how to produce statistics with certain software packages, but as a way of illuminating the underlying logic behind the symbols.

The limited statistical knowledge that students gain from straight forward ′how-to′ books makes it very hard for students to move beyond introductory statistics courses to postgraduate study and research. This book should help to bridge this gap.