Quantitative Data Analysis with Minitab

A Guide for Social Scientists
1. Auflage 1996
ISBN: 978-0-415-12324-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 302 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 363 g

Quantitative data analysis is now a compulsory component of most degree courses in the social sciences and students are increasingly reliant on computers for the analysis of data. Quantitative Data Analysis with Minitab explains statistical tests for Minitab users using the same formulae free, non technical approach, as the very successful SPPS version.
Students will learn a wide range of quantitative data analysis techniques and become familiar with how these techniques can be implemented through the latest version of Minitab. Techniques covered include univariate analysis (with frequency table, dispersion and histograms), bivariate (with contingency tables correlation, analysis of varience and non-parametric tests) and multivariate analysis (with multiple regression, path analysis, covarience and factor analysis). In addition the book covers issues such as sampling, statistical significance, conceptualisation and measurement and the selection of appropriate tests. Each chapter concludes with a set of exercises.
Social science students will welcome this integrated, non mathematical introduction to quantitative data anlysis and the minitab package.

Autoren/Hrsg.

Bryman, Alan

Cramer, Duncan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Automatische Datenerfassung, Datenanalyse
• Mathematik | Informatik EDV | Informatik Betriebssysteme Mac OS, Mac OS X
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Gesellschaftstheorie
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik

Inhaltsverzeichnis

Preface. Data Analysis and the Research Process. Analysing Data with Computers: First Steps with Minitab. Analysing Data with Computers: Further Steps with Minitab. Concepts and their Measurement. Summarising Data. Sampling and Statistical Significance. Bivariate Analysis: Exploring Differences between Scores on Two Variables. Bivariate Analysis: Exploring Relationships between Two Variables. Multivariate Analysis: Exploring Differences among Three or more Variables. Multivariate Analysis: Exploring Relationships among Three or More Variables. Aggregating Variables: Exploratory Factor Analysis. Appendices. Answers to Questions. Bibliography. Index

Über Autor(innen)

Alan Bryman, Duncan Cramer