Title: Using statistics to make educational decisions /
Authors: Tanner, David.
Publisher: Sage,
Year: 2012
Subjects: Schulleistungsmessung.; Educational statistics Study and teaching.; Educational tests and measurements
Abstract: Government scrutiny and intensified oversight have dramatically changed the landscape of education in recent years. Observers want to know how schools compare, which states are spending the most per student, whether reforms are making a difference, and why so many students are struggling. Some of these questions require technical answers that educators historically redirected to outside experts, but the questions leveled at all educators have become so acute and persistent that they can no longer be outsourced. This text helps educators develop the tools and the conceptual understanding needed to provide definitive answers to difficult statistical questions facing education today. Key features: * An interdisciplinary approach provides a wealth of examples psychology, educational administration, teacher education, special education, adult education, counselor education and more. * Thinking logically is emphasized, aiding those students with little background in formal mathematics. * Each chapter opens with a typical problem facing educators, outlines options for responding, explores each option, and ends with a summary. * Through a wider lens features show a broad application of a particular subject, illustrating how to execute a statistical concept or idea. * Chapters include data sets drawn from actual school practice in SPSS format. * Designed to help students master the language of statistics, key terms are bold-face, defined in the text, redefined in a text box later in the chapter, and included in the Glossary. * Includes an introduction to measurement concepts, multiple regression, and selected advance statistical procedures. * Chapter 15 focuses on government involvement and the associated emphasis on standardized testing.
Contents: A context for solving quantitative problems -- Describing data -- Data distributions: picturing statistics -- Working with the normal curve: z scores -- Probability and the normal distribution -- t for one, or two -- One-way analysis of variance -- The factorial ANOVA -- Dependent groups tests for interval data -- Correlation -- Regression with one predictor -- Regression with more than one predictor -- Some of the chi-square tests -- Working with ordinal, more-, or less-than data -- Testing issues -- A brief introduction to selected advanced topics -- Glossary -- Appendices.