Nonparametric Statistics For Social And Behavioral Sciences
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Nonparametric Statistics for the Behavioral Sciences by Sidney Siegel Pdf
The use of statistical tests in research; Choosing an appropriate statistical test; The one-sample case; The case of two related samples; The case of two independent samples; The case of k related samples; The case of k independent samples; Measures of correlatin and their tests of significance.
Nonparametric Statistics for Social and Behavioral Sciences by M. Kraska-MIller Pdf
Incorporating a hands-on pedagogical approach, Nonparametric Statistics for Social and Behavioral Sciences presents the concepts, principles, and methods used in performing many nonparametric procedures. It also demonstrates practical applications of the most common nonparametric procedures using IBM’s SPSS software. This text is the only current nonparametric book written specifically for students in the behavioral and social sciences. Emphasizing sound research designs, appropriate statistical analyses, and accurate interpretations of results, the text: Explains a conceptual framework for each statistical procedure Presents examples of relevant research problems, associated research questions, and hypotheses that precede each procedure Details SPSS paths for conducting various analyses Discusses the interpretations of statistical results and conclusions of the research With minimal coverage of formulas, the book takes a nonmathematical approach to nonparametric data analysis procedures and shows students how they are used in research contexts. Each chapter includes examples, exercises, and SPSS screen shots illustrating steps of the statistical procedures and resulting output.
Nonparametric Statistics for the Behavioral Sciences by Sidney Siegel,N. John Castellan Pdf
Revision of the classic text in the field, adding two new chapters and thoroughly updating all others. The original structure is retained, and the book continues to serve as a combined text/reference.
Statistics for International Social Work And Other Behavioral Sciences by Serge Lee,Maria Cesaltina da Silveira Nunes Dinis,Lois Lowe,Kelly Anders Pdf
Statistics for International Social Work And Other Behavioral Sciences presents statistics using straightforward, accessible language, making it easier for students of all backgrounds -- particularly social work student undergraduates, graduates and practitioners -- to learn and apply statistical concepts, tools, and procedures. The book incorporates two powerful statistical software programs, Statistical Package for the Social Sciences (SPSS) and Microsoft Excel ToolPak, into statistical computations. The course contents have been organized pedagogically in an order that allows students to view the progression of concepts and hand calculations in conjunction with computerized statistical analysis tools. Furthermore, this text is unique in that it includes appendices specifically designed to provide instructions on preparing data for data entry, construct variable names, and data analysis-using SPSS; present guidelines to nonparametric statistics and post hoc comparisons; and focus on Microsoft Excel ToolPak, which is available in most personally owned computers and handheld devices such as tablets and smart phones. The book also includes robust instructor and student materials via a companion website.
Essentials of Statistics for the Social and Behavioral Sciences by Barry H. Cohen,R. Brooke Lea Pdf
Master the essential statistical skills used in social andbehavioral sciences Essentials of Statistics for the Social and Behavioral Sciencesdistills the overwhelming amount of material covered inintroductory statistics courses into a handy, practical resourcefor students and professionals. This accessible guide covers basicto advanced concepts in a clear, concrete, and readablestyle. Essentials of Statistics for the Social and Behavioral Sciencesguides you to a better understanding of basic concepts ofstatistical methods. Numerous practical tips are presented forselecting appropriate statistical procedures. In addition, thisuseful guide demonstrates how to evaluate and interpret statisticaldata, provides numerous formulas for calculating statistics fromtables of summary statistics, and offers a variety of workedexamples. As part of the Essentials of Behavioral Science series, this bookoffers a thorough review of the most relevant statistical conceptsand techniques that will arm you with the tools you'll need forknowledgeable, informed practice. Each concise chapter featuresnumerous callout boxes highlighting key concepts, bulleted points,and extensive illustrative material, as well as "Test Yourself"questions that help you gauge and reinforce your grasp of theinformation covered.
Modern Statistics for the Social and Behavioral Sciences by Rand Wilcox Pdf
In addition to learning how to apply classic statistical methods, students need to understand when these methods perform well, and when and why they can be highly unsatisfactory. Modern Statistics for the Social and Behavioral Sciences illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques. Numerous illustrations provide a conceptual basis for understanding why practical problems with classic methods were missed for so many years, and why modern techniques have practical value. Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: Early studies seemed to suggest that normality can be assumed with relatively small sample sizes due to the central limit theorem. However, crucial issues were missed. Vastly improved methods are now available for dealing with non-normality. The impact of outliers and heavy-tailed distributions on power and our ability to obtain an accurate assessment of how groups differ and variables are related is a practical concern when using standard techniques, regardless of how large the sample size might be. Methods for dealing with this insight are described. The deleterious effects of heteroscedasticity on conventional ANOVA and regression methods are much more serious than once thought. Effective techniques for dealing heteroscedasticity are described and illustrated. Requiring no prior training in statistics, Modern Statistics for the Social and Behavioral Sciences provides a graduate-level introduction to basic, routinely used statistical techniques relevant to the social and behavioral sciences. It describes and illustrates methods developed during the last half century that deal with known problems associated with classic techniques. Espousing the view that no single method is always best, it imparts a general understanding of the relative merits of various techniques so that the choice of method can be made in an informed manner.
Author : Jared A. Linebach,Brian P. Tesch,Lea M. Kovacsiss Publisher : Springer Science & Business Media Page : 416 pages File Size : 44,5 Mb Release : 2013-11-19 Category : Mathematics ISBN : 9781461490418
Nonparametric Statistics for Applied Research by Jared A. Linebach,Brian P. Tesch,Lea M. Kovacsiss Pdf
Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in "ordinal" data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine. This is a textbook on non-parametric statistics for applied research. The authors propose to use a realistic yet mostly fictional situation and series of dialogues to illustrate in detail the statistical processes required to complete data analysis. This book draws on a readers existing elementary knowledge of statistical analyses to broaden his/her research capabilities. The material within the book is covered in such a way that someone with a very limited knowledge of statistics would be able to read and understand the concepts detailed in the text. The “real world” scenario to be presented involves a multidisciplinary team of behavioral, medical, crime analysis, and policy analysis professionals work together to answer specific empirical questions regarding real-world applied problems. The reader is introduced to the team and the data set, and through the course of the text follows the team as they progress through the decision making process of narrowing the data and the research questions to answer the applied problem. In this way, abstract statistical concepts are translated into concrete and specific language. This text uses one data set from which all examples are taken. This is radically different from other statistics books which provide a varied array of examples and data sets. Using only one data set facilitates reader-directed teaching and learning by providing multiple research questions which are integrated rather than using disparate examples and completely unrelated research questions and data.
Fundamental Statistics for the Social and Behavioral Sciences by Howard T. Tokunaga Pdf
Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas. Students learn not only how to calculate statistics, but also how to interpret and communicate the results of statistical analyses in light of a study’s research hypothesis. Featuring accessible writing and well-integrated research examples, the book gives students a greater understanding of how research studies are conceived, conducted, and communicated. The Second Edition includes a new chapter on regression; covers how collected data can be organized, presented and summarized; the process of conducting statistical analyses to test research questions, hypotheses, and issues/controversies; and examines statistical procedures used in research situations that vary in the number of independent variables in the study. Every chapter includes learning checks, such as review questions and summary boxes, to reinforce the content students just learned, and exercises at the end of every chapter help assess their knowledge. Also new to the Second Edition -- animated video tutorials!
Statistical Power Analysis for the Behavioral Sciences by Jacob Cohen Pdf
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Nonparametric Statistics for Non-Statisticians by Gregory W. Corder,Dale I. Foreman Pdf
A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences. Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS® screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields. Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to: Test data for normality and randomness Use the Wilcoxon signed rank test to compare two related samples Apply the Mann-Whitney U test to compare two unrelated samples Compare more than two related samples using the Friedman test Employ the Kruskal-Wallis H test to compare more than two unrelated samples Compare variables of ordinal or dichotomous scales Test for nominal scale data A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS®, and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice. Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.
