Best Practices in Quantitative Methods

Best Practices in Quantitative Methods
Author :
Publisher : SAGE
Total Pages : 609
Release :
ISBN-10 : 9781412940658
ISBN-13 : 1412940656
Rating : 4/5 (656 Downloads)

Book Synopsis Best Practices in Quantitative Methods by : Jason W. Osborne

Download or read book Best Practices in Quantitative Methods written by Jason W. Osborne and published by SAGE. This book was released on 2008 with total page 609 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.


Best Practices in Quantitative Methods Related Books

Best Practices in Quantitative Methods
Language: en
Pages: 609
Authors: Jason W. Osborne
Categories: Social Science
Type: BOOK - Published: 2008 - Publisher: SAGE

DOWNLOAD EBOOK

The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible,
Best Practices in Data Cleaning
Language: en
Pages: 297
Authors: Jason W. Osborne
Categories: Mathematics
Type: BOOK - Published: 2013 - Publisher: SAGE

DOWNLOAD EBOOK

Many researchers jump straight from data collection to data analysis without realizing how analyses and hypothesis tests can go profoundly wrong without clean d
Teaching Quantitative Methods
Language: en
Pages: 201
Authors: Geoff Payne
Categories: Social Science
Type: BOOK - Published: 2011-03-04 - Publisher: SAGE

DOWNLOAD EBOOK

This exciting collection is both useful and timely. It clearly lays out the problems, strategies and resources associated with the teaching of quantitative meth
Research Design
Language: en
Pages: 305
Authors: John W. Creswell
Categories: Reference
Type: BOOK - Published: 2014 - Publisher: SAGE

DOWNLOAD EBOOK

The bestseller that pioneered the comparison of qualitative, quantitative, and mixed methods research design continues in its Fourth Edition to help students an
Regression & Linear Modeling
Language: en
Pages: 489
Authors: Jason W. Osborne
Categories: Psychology
Type: BOOK - Published: 2016-03-24 - Publisher: SAGE Publications

DOWNLOAD EBOOK

In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become fa