This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way. It is chock full of practical examples and tips on how to analyze and report research results using these techniques. The book is invaluable to readers interested in meeting the new APA Publication Manual guidelines by adopting the new statistics - which are more informative than null hypothesis significance testing, and becoming widely used in many disciplines. Accompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book’s exercises use ESCI's simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice. The book’s pedagogical program, built on cognitive science principles, reinforces learning: Boxes provide "evidence-based" advice on the most effective statistical techniques. Numerous examples reinforce learning, and show that many disciplines are using the new statistics. Graphs are tied in with ESCI to make important concepts vividly clear and memorable. Opening overviews and end of chapter take-home messages summarize key points. Exercises encourage exploration, deep understanding, and practical applications. This highly accessible book is intended as the core text for any course that emphasizes the new statistics, or as a supplementary text for graduate and/or advanced undergraduate courses in statistics and research methods in departments of psychology, education, human development , nursing, and natural, social, and life sciences. Researchers and practitioners interested in understanding the new statistics, and future published research, will also appreciate this book. A basic familiarity with introductory statistics is assumed.
This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’).
A jargon-free introduction for students and researchers looking to interpret the practical significance of their results.
Pearson's product moment coefficient is a parametric correlation which expresses the relationship between two numerical continuous variables . If there is at least one dichotomous variable , the point biserial is appropriate .
Unlike other statistics books, this text explains what statistics mean and how they are used, rather than how to calculate them. The book walks readers through basic concepts as well as some of the most complex statistical models in use.
... L. 267 Patton, M.Q. 248 Pearson's r 173, 182, 183, 212, 380 Peltonen, T. 267 Perfetti, C.A. 123, 126 Perkins, ... 380 Platania, J. 109 platykurtic kurtosis 81 point-biserial correlation 181–2 police, power of 290–1 Popper, K.R. 9, ...
The only introduction to statistics book written specifically for political science undergraduates, this book explains each statistical concept in plain language—from basic univariate statistics and the basic measures of association to ...
Enabling your students to answer the why behind statistical methods, this text teaches them how to successfully draw conclusions when the premises are flawed.
What is a p-value Anyway? offers a fun introduction to the fundamental principles of statistics, presenting the essential concepts in thirty-four brief, enjoyable stories. Drawing on his experience...
For a standard two sample t-test, the signal to noise ratio is called Cohen's d, which is estimated from data as (see Chap. 3): d = . Cohen's d tells you how easily you can discriminate different means. The mean difference is in the ...
Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, ...