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Making Sense Of Statistical Methods In Social Research

Making Sense Of Statistical Methods In Social Research

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  • ISBN:9781847872876
  • Editorial: Sage Publications
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  • Nº Pág.:216
  • Idiomas:Ingles

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"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.

The position of statistical methods in social research 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

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