Statistical Modelling For Social Researchers: Principles And Practice (social Research Today)
by Roger Tarling /
2008 / English / PDF
5.6 MB Download
This book explains the principles and theory of statistical
modelling in an intelligible way for the non-mathematical social
scientist looking to apply statistical modelling techniques in
research. The book also serves as an introduction for those
wishing to develop more detailed knowledge and skills in
statistical modelling. Rather than present a limited number of
statistical models in great depth, the aim is to provide a
comprehensive overview of the statistical models currently
adopted in social research, in order that the researcher can make
appropriate choices and select the most suitable model for the
research question to be addressed. To facilitate application, the
book also offers practical guidance and instruction in fitting
models using SPSS and Stata, the most popular statistical
computer software which is available to most social researchers.
Instruction in using MLwiN is also given.
This book explains the principles and theory of statistical
modelling in an intelligible way for the non-mathematical social
scientist looking to apply statistical modelling techniques in
research. The book also serves as an introduction for those
wishing to develop more detailed knowledge and skills in
statistical modelling. Rather than present a limited number of
statistical models in great depth, the aim is to provide a
comprehensive overview of the statistical models currently
adopted in social research, in order that the researcher can make
appropriate choices and select the most suitable model for the
research question to be addressed. To facilitate application, the
book also offers practical guidance and instruction in fitting
models using SPSS and Stata, the most popular statistical
computer software which is available to most social researchers.
Instruction in using MLwiN is also given.
Models covered in the book include; multiple regression, binary,
multinomial and ordered logistic regression, log-linear models,
multilevel models, latent variable models (factor analysis), path
analysis and simultaneous equation models and models for
longitudinal data and event histories. An accompanying website
hosts the datasets and further exercises in order that the reader
may practice developing statistical models.
Models covered in the book include; multiple regression, binary,
multinomial and ordered logistic regression, log-linear models,
multilevel models, latent variable models (factor analysis), path
analysis and simultaneous equation models and models for
longitudinal data and event histories. An accompanying website
hosts the datasets and further exercises in order that the reader
may practice developing statistical models.
An ideal tool for postgraduate social science students, research
students and practicing social researchers in universities,
market research, government social research and the voluntary
sector.
An ideal tool for postgraduate social science students, research
students and practicing social researchers in universities,
market research, government social research and the voluntary
sector.
