Using Statistics In Social Research: A Concise Approach
by Scott M. Lynch /
2013 / English / PDF
4.9 MB Download
This book covers applied statistics for the social sciences with
upper-level undergraduate students in mind. The chapters are
based on lecture notes from an introductory statistics course the
author has taught for a number of years. The book integrates
statistics into the research process, with early chapters
covering basic philosophical issues underpinning the process of
scientific research. These include the concepts of deductive
reasoning and the falsifiability of hypotheses, the development
of a research question and hypotheses, and the process of data
collection and measurement. Probability theory is then covered
extensively with a focus on its role in laying the foundation for
statistical reasoning and inference. After illustrating the
Central Limit Theorem, later chapters address the key, basic
statistical methods used in social science research, including
various z and t tests and confidence intervals, nonparametric chi
square tests, one-way analysis of variance, correlation,
simple regression, and multiple regression, with a discussion of
the key issues involved in thinking about causal
processes. Concepts and topics are illustrated using both
real and simulated data. The penultimate chapter presents
rules and suggestions for the successful presentation of
statistics in tabular and graphic formats, and the final chapter
offers suggestions for subsequent reading and study.
This book covers applied statistics for the social sciences with
upper-level undergraduate students in mind. The chapters are
based on lecture notes from an introductory statistics course the
author has taught for a number of years. The book integrates
statistics into the research process, with early chapters
covering basic philosophical issues underpinning the process of
scientific research. These include the concepts of deductive
reasoning and the falsifiability of hypotheses, the development
of a research question and hypotheses, and the process of data
collection and measurement. Probability theory is then covered
extensively with a focus on its role in laying the foundation for
statistical reasoning and inference. After illustrating the
Central Limit Theorem, later chapters address the key, basic
statistical methods used in social science research, including
various z and t tests and confidence intervals, nonparametric chi
square tests, one-way analysis of variance, correlation,
simple regression, and multiple regression, with a discussion of
the key issues involved in thinking about causal
processes. Concepts and topics are illustrated using both
real and simulated data. The penultimate chapter presents
rules and suggestions for the successful presentation of
statistics in tabular and graphic formats, and the final chapter
offers suggestions for subsequent reading and study.