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This mid-level book introduces and explains statistical concepts and principles clearly, assuming minimal mathematical sophistication but avoiding a "cookbook" approach. The book also presents a broader outlook on hypothesis testing by including such often-neglected concepts as statistical power, indices and other techniques.
A comprehensive and user-friendly introduction to statistics-now revised and updated Introductory Statistics for the Behavioral Sciences has had a long and successful history and is a popular and well-respected statistics text. Now in its sixth edition, the text has been thoroughly revised to present all the topics students in the behavioral sciences need in a uniquely accessible format that aids in the comprehension and implementation of the statistical analyses most commonly used in the behavioral sciences. Using a continuous narrative that explains statistics and tracks a common data set throughout, the authors have developed an innovative approach that makes the material unintimidating and memorable, providing a framework that connects all of the topics in the text and allows for easy comparison of different statistical analyses. New features in this Sixth Edition include: * Different aspects of a common data set are used to illustrate the various statistical methods throughout the text, with an emphasis on drawing connections between seemingly disparate statistical procedures and formulas * Computer exercises based on the same large data set and relevant to that chapter's content. The data set can be analyzed by any available statistical software * New "Bridge to SPSS" sections at the end of each chapter explain, for those using this very popular statistical package, how to perform that chapter's statistical procedures by computer, and how to translate the output from SPSS * New chapters on multiple comparisons and repeated-measures ANOVA
In this fully updated edition of Using Basic Statistics in the Behavioral and Social Sciences, Annabel Ness Evans presents introductory statistics in a practical, conceptual, and humorous way, reducing the anxiety that many students experience in introductory courses. Avoiding complex notation and derivations, the book focuses on helping readers develop an understanding of the underlying logic of statistics, rather than rote memorization. Focus on Research boxes engage students with realistic applications of statistics, and end-of-chapter exercises ensure student comprehension. This exciting new edition includes a greater number of realistic and engaging global examples within the social and behavioral sciences, making it ideal for use within many departments or in interdisciplinary settings.
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.
This brief version of Gravetter and Wallnau’s proven best seller offers the straightforward instruction, accuracy, built-in learning aids, and wealth of real-world examples that professors AND students have come to appreciate. The authors take time to explain statistical procedures so that students can go beyond memorizing formulas and begin gaining a conceptual understanding of statistics. To ensure that even students with a weak background in mathematics can understand statistics, the authors skillfully integrate applications that reinforce concepts. The authors take care to show students how having an understanding of statistical procedures will help them comprehend published findings and will lead them to become savvy consumers of information. Known for its exceptional accuracy and examples, this text also has a complete supplements package to support instructors with class preparation and testing. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Introductory Statistics for the Behavioral Sciences provides an introduction to statistical concepts and principles. This book emphasizes the robustness of parametric procedures wherein such significant tests as t and F yield accurate results even if such assumptions as equal population variances and normal population distributions are not well met. Organized into three parts encompassing 16 chapters, this book begins with an overview of the rationale upon which much of behavioral science research is based, namely, drawing inferences about a population based on data obtained from a sample. This text then examines the primary goal of descriptive statistics to bring order out of chaos. Other chapters consider the concept of variability and its applications. This book discusses as well the essential characteristics of a group of scores. The final chapter deals with the chi-square analysis. This book is a valuable resource for students of statistics as well as for undergraduates majoring in psychology, sociology, and education.
FUNDAMENTAL STATISTICS FOR THE BEHAVIORAL SCIENCES focuses on providing the context of statistics in behavioral research, while emphasizing the importance of looking at data before jumping into a test. This practical approach provides students with an understanding of the logic behind the statistics, so they understand why and how certain methods are used -- rather than simply carry out techniques by rote. Students move beyond number crunching to discover the meaning of statistical results and appreciate how the statistical test to be employed relates to the research questions posed by an experiment. Written in an informal style, the text provides an abundance of real data and research studies that provide a real-life perspective and help students learn and understand concepts. In alignment with current trends in statistics in the behavioral sciences, the text emphasizes effect sizes and meta-analysis, and integrates frequent demonstrations of computer analyses through SPSS and R. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
For the first course in statistics, this basic, comprehensive introductory text covers topics in conventional order, starting with descriptive statistics and ending with inferential statistics.
