Book•
Discovering Statistics Using SPSS
01 Jan 2000-
TL;DR: Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS(R).
Abstract: Hot on the heels of the 3rd edition of Andy Field's award-winning Discovering Statistics Using SPSS comes this brand new version for students using SAS(R). Andy has teamed up with a co-author, Jeremy Miles, to adapt the book with all the most up-to-date commands and programming language from SAS(R) 9.2. If you're using SAS(R), this is the only book on statistics that you will need! The book provides a comprehensive collection of statistical methods, tests and procedures, covering everything you're likely to need to know for your course, all presented in Andy's accessible and humourous writing style. Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS(R). A 'cast of characters' supports the learning process throughout the book, from providing tips on how to enter data in SAS(R) properly to testing knowledge covered in chapters interactively, and 'real world' and invented examples illustrate the concepts and make the techniques come alive. The book's companion website (see link above) provides students with a wide range of invented and real published research datasets. Lecturers can find multiple choice questions and PowerPoint slides for each chapter to support their teaching.
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TL;DR: The aim of this commentary is to overview checking for normality in statistical analysis using SPSS.
Abstract: Statistical errors are common in scientific literature and about 50% of the published articles have at least one error. The assumption of normality needs to be checked for many statistical procedures, namely parametric tests, because their validity depends on it. The aim of this commentary is to overview checking for normality in statistical analysis using SPSS.
2,782Â citations
01 Oct 2013
TL;DR: An overview of the statistical technique and how it is used in various research designs and applications is given, to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.
Abstract: The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.
2,214Â citations
TL;DR: In this article, the authors examined the relative impact of different types of leadership on students' academic and non-academic outcomes and concluded that the average effect of instructional leadership on student outcomes was three to four times that of transformational leadership.
Abstract: Purpose: The purpose of this study was to examine the relative impact of different types of leadership on students' academic and nonacademic outcomes.Research Design:The methodology involved an analysis of findings from 27 published studies of the relationship between leadership and student outcomes. The first meta-analysis, including 22 of the 27 studies, involved a comparison of the effects of transformational and instructional leadership on student outcomes. The second meta-analysis involved a comparison of the effects of five inductively derived sets of leadership practices on student outcomes. Twelve of the studies contributed to this second analysis.Findings: The first meta-analysis indicated that the average effect of instructional leadership on student outcomes was three to four times that of transformational leadership. Inspection of the survey items used to measure school leadership revealed five sets of leadership practices or dimensions: establishing goals and expectations; resourcing strategi...
2,112Â citations
TL;DR: In this paper, the authors explored the role of four key factors that influence perceptions of trust and consumer choice within a hotel context, and found that consumers tend to rely on easy-to-process information, when evaluating a hotel based upon reviews.
1,250Â citations
TL;DR: Investigation of how personality influences usage or non-usage of Facebook showed that Facebook users tend to be more extraverted and narcissistic, but less conscientious and socially lonely, than nonusers.
1,118Â citations