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Guide for Statistical Tests and Interpretations with SPSS [Pehme köide]

  • Formaat: Paperback / softback, 224 pages, kõrgus x laius: 254x178 mm, kaal: 512 g, 9 Tables, black and white; 17 Line drawings, black and white; 101 Halftones, black and white; 118 Illustrations, black and white
  • Ilmumisaeg: 29-Oct-2024
  • Kirjastus: Routledge
  • ISBN-10: 1032102101
  • ISBN-13: 9781032102108
Teised raamatud teemal:
Guide for Statistical Tests and Interpretations with SPSSSuurem pilt
  • Formaat: Paperback / softback, 224 pages, kõrgus x laius: 254x178 mm, kaal: 512 g, 9 Tables, black and white; 17 Line drawings, black and white; 101 Halftones, black and white; 118 Illustrations, black and white
  • Ilmumisaeg: 29-Oct-2024
  • Kirjastus: Routledge
  • ISBN-10: 1032102101
  • ISBN-13: 9781032102108
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781032102108.html
Märksõnad:

A Guide for Statistical Tests and Interpretations with SPSS is designed for students taking basic and advanced courses in statistics, taking an integrative and practical approach to learning statistics. It guides students through navigating SPSS outputs and writing quantitatively, dealing with technical and substantive interpretations without resorting to complex mathematical formulae.

Starting from the basics of quantitative research methods and discussing descriptive and inferential statistical tests, this book provides a unique perspective of data analysis with SPSS. It makes a conscious effort to explore the various statistical methods one can use to dissect a data set using basic or advanced statistical techniques to achieve the best outcome. It covers the practical questions that arise while doing an assignment, final paper, or thesis – showing students how to proceed to the next step in their interpretation and analysis. It will provide quantitative methodology or data analysis students with core interpretations of SPSS outputs for key statistical tests. It will also demonstrate how to select and report the key trends and patterns of the data using descriptive and inferential statistics, the requirements and/or assumptions of each test, as well as the precise language to use for reporting on each test.

With SPSS screenshots and step-by-step advice, this book will be useful for all undergraduate and graduate students in the social sciences and humanities, as a supplemental textbook to provide practical guidance on moving through all steps of statistical testing and analysis.



This book is designed for students taking basic and advanced courses in statistics, taking an integrative and practical approach to learning statistics. It guides students through navigating SPSS outputs and writing quantitatively, dealing with technical and substantive interpretations without resorting to complex mathematical formulae.

Part 1: Introduction To Quantitative Research Methods, Data Modification & Descriptive Statistics
1. Understanding Quantitative Research as a Precursor to the Statistical Pathways
2. Data Manipulation & Sample Modification Techniques
3. Describing Trends and Patterns of the Data Using Univariate Statistics
4. Bivariate and Multivariate Descriptive Statistics Using Non-Parametric Tests; Part 2: Inferential Statistical Analyses Using Hypothesis Testing, Comparison of Means Tests & Average Differences
5. Introduction to Inferential Statistics and Understanding the Nuances of Inference based Testing and Generalizability of Data
6. Bivariate Hypothesis Testing Using an Independent Samples Comparison of Means t-test using a Dichotomous Independent Variable
7. Bivariate Hypothesis Testing Using Comparison of Means using More than Two Groups, One-Way ANOVA
8. Multivariate Hypothesis Testing Using Comparison of Means using Two-Way Factorial ANOVA
9. Multivariate Hypothesis Testing Using Comparison of Means by Advanced ANOVA Statistical Hypothesis Testing using ANCOVA, MANOVA, MANCOVA; Part 3: Inferential Statistics with A Focus on Associations & Predictions Using Correlation & Regression Models
10. Correlations with Interval-Ratio Continuous Data
11. A World of Prediction(s) Using Regression Analyses: Multiple Linear Regression, Hierarchical Regression, and Logistic Regression; APPENDIX A: Revised Tables for Peer Reviewed Articles, Theses, or Dissertations

Arshia U. Zaidi is an Associate Professor in the Faculty of Social Science & Humanities Criminology & Justice at Ontario Tech University (OTU), Canada, teaching statistics to both undergraduate and graduate students.