Muutke küpsiste eelistusi

E-raamat: Quantitative Data Analysis with Minitab: A Guide for Social Scientists [Taylor & Francis e-raamat]

(Loughborough University, UK), (University of Leicester, UK)
  • Formaat: 302 pages
  • Ilmumisaeg: 06-Jun-1996
  • Kirjastus: Routledge
  • ISBN-13: 9780203360217
  • Taylor & Francis e-raamat
  • Hind: 133,87 €*
  • * hind, mis tagab piiramatu üheaegsete kasutajate arvuga ligipääsu piiramatuks ajaks
  • Tavahind: 191,24 €
  • Säästad 30%
Quantitative Data Analysis with Minitab: A Guide for Social Scientists
  • Formaat: 302 pages
  • Ilmumisaeg: 06-Jun-1996
  • Kirjastus: Routledge
  • ISBN-13: 9780203360217
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.
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