2016

International Statistical Review, 2010

Table of contents 1. Linear models: some historical perspectives 8. Balanced linear models 2. Basic elements of linear algebra 9. The adequacy of Satterthwaite's approximation 3. Basic concepts in matrix algebra 10. Unbalanced fixed-effects models 4. The multivariate normal distribution 11. Unbalanced random and mixed models 5. Quadratic forms in normal variables 12. Additional topics in linear models 6. Full rank linear models 13. Generalized linear models 7. Less-than-full-rank linear models Readership: All readers interested in regression presented with a mix of theory and practice. The material on which this book is based has been taught in a couple of courses at the University of Florida for about 20 years and the author's skills and experience in doing this are superbly represented in this fine text. The presentation itself leans more toward the theoretical aspects, but there are numerous exercises that reinforce both the theoretical and the practical aspects of regression. (However, no solutions are provided.) "Chapters 11 and 12 can be particularly helpful to graduate students looking for dissertation topics." (Preface) This is an excellent, reliable, and comprehensive text.

Journal of Humanities and Applied Social Sciences

Purpose The purpose this paper is to review some of the statistical methods used in the field of social sciences. Design/methodology/approach A review of some of the statistical methodologies used in areas like survey methodology, official statistics, sociology, psychology, political science, criminology, public policy, marketing research, demography, education and economics. Findings Several areas are presented such as parametric modeling, nonparametric modeling and multivariate methods. Focus is also given to time series modeling, analysis of categorical data and sampling issues and other useful techniques for the analysis of data in the social sciences. Indicative references are given for all the above methods along with some insights for the application of these techniques. Originality/value This paper reviews some statistical methods that are used in social sciences and the authors draw the attention of researchers on less popular methods. The purpose is not to give technical d...

Course Abstract by: Bernhard Kittel This outline is for a course I attended. The course provided a concise introduction to fundamental ideas of descriptive and inferential statistics with the intention to help participants understanding and applying the logic of quantitative analysis in political and social science. It covers the basic concepts of statistics, probability, and test theory. Methods of bi-variate analysis were discussed for nominal, ordinal, and interval-scaled variables, and the basic idea of linear regression analysis were introduced. This course introduced students to using the system ‘R’ as part of its practical application of the course material covered. For more information, please refer to the attached pdf document from ECPR and the lecturer which contains the course syllabus information provided on the course website. No copyright infringement intended.

2011

The Creditable Postgraduate Seminar tries to give an answer to the growing demand on training and practice in quantitative analysis for researchers and professionals of the Social Sciences. The pedagogic proposal points the training of theoretical-practice data analysis, linking the acquisition of statistical concepts to the application on reference material that it “makes sense ” for the professional field of the Social Sciences. For the practical training the methodological material used is brought by the tutor and the databases are national surveys on conditions of life in urban homes of the Argentina Republic. This integrated approach of social data analysis coming from surveys, tries to enable professionals from this area to use in a critical way official databases that are of public access. In this paper we present some results from our experience of a course for Undergraduates that was given in our University. JUSTIFICATION The design and development of Creditable Postgraduat...

Today the use of statistics has evolved far beyond its genesis. The use of statistics by individuals and organisations has become ubiquitous, leading to a wider informed knowledge-base that starts from the process to gather and understand the data up to the end phase where informed decisions need to be made. This is the case across the different thematic domains ranging from the natural and social sciences, medicine, business, and other areas. Statistics can be used and unfortunately, abused; the latter leading to the generation of serious errors in both description and analysis, in turn leading to misleading interpretations. Few are immune to such error generation and the need is felt to ensure that we are aware of the responsibilities researchers have in generating statistics. Therefore, when the National Statistics Office was approached, early in 2010, by a group of researchers to assist in publishing a book on statistics intended for persons who are non-conversant with this discipline, I readily accepted, as they had found a niche I believe was untapped locally. This idea was appropriately launched during a World Statistics Day seminar, marked for the first time ever on 20 October 2010. The feedback was positive and encouraging. This book introduces statistics to higher education students who are not necessarily mathematically oriented, and whose perception of statistics may be tinged with fear. Its scope is not to review equations and formulae, but to outline the importance of the strict rules that govern research methodology and the sound interpretation of results. In other words, it identifies uses and abuses of statistics, and is a useful text even for those who may eventually specialise in statistics. In many respects, therefore, it is different from other mainstream statistics textbooks. While the views expressed by the book's authors do not necessarily reflect NSO's official stance, such initiatives are to be commended as they help promote statistics, which are so vital in today's day and age. The ultimate aim of this publication is to educate, and to promote statistical literacy. This forms an intrinsic part of NSO's long-term vision.

2009

According to Méndez Ramírez(1) “Statistics becomes an aid to the process of scientific research; however, in order to be effective differences between what is statistics and the science on which it is applied must be cleared. That is to say, the approaches of assumptions, ...

2010

Over the years, mathematics and statistics have become increasingly important in the social sciences1. A look at the history quickly confirms this claim. At the beginning of the 20th century most theories in the social sciences were formulated in qualitative terms while quantitative methods did not play a substantial role in the formulation and establishment of them. Moreover, many practitioners considered mathematical methods to be inappropriate and simply not suited to foster our understanding of the social domain.

2018

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. Summary Some current aspects of statistical work are reviewed undeir three broad headings, applied probability modelling, design of investigations and statistical analysis and interpretation of data. The emphasis is on applications in science and scienice-based technology, although some incidental comments are made about statistics in public affairs. While no technical details are given, there is some discussion of potential fields for development. The choice of topics reflects the author's personal interests.