Guide to Analysis


Book Description

This textbook is part of a major series designed to guide undergraduate students through the first year of their mathematics course. New concepts are introduced gradually with worked examples as illustrations. Exercises with and without solutions are provi




Survey Scales


Book Description

Synthesizing the literature from the survey and measurement fields, this book explains how to develop closed-response survey scales that will accurately capture such constructs as attitudes, beliefs, or behaviors. It provides guidelines to help applied researchers or graduate students review existing scales for possible adoption or adaptation in a study; create their own conceptual framework for a scale; write checklists, true-false variations, and Likert-style items; design response scales; examine validity and reliability; conduct a factor analysis; and document the instrument development and its technical quality. Advice is given on constructing tables and graphs to report survey scale results. Concepts and procedures are illustrated with "Not This/But This" examples from multiple disciplines. User-Friendly Features *End-of-chapter exercises with sample solutions, plus annotated suggestions for further reading. *"Not This/But This" examples of poorly written and strong survey items. *Chapter-opening overviews and within-chapter summaries. *Glossary of key concepts. *Appendix with examples of parametric and nonparametric procedures for group comparisons.




How to Use SPSS®


Book Description

How to Use SPSS® is designed with the novice computer user in mind and for people who have no previous experience of using SPSS. Each chapter is divided into short sections that describe the statistic being used, important underlying assumptions, and how to interpret the results and express them in a research report. The book begins with the basics, such as starting SPSS, defining variables, and entering and saving data. It covers all major statistical techniques typically taught in beginning statistics classes, such as descriptive statistics, graphing data, prediction and association, parametric inferential statistics, nonparametric inferential statistics and statistics for test construction. More than 250 screenshots (including sample output) throughout the book show students exactly what to expect as they follow along using SPSS. The book includes a glossary of statistical terms and practice exercises. A complete set of online resources including video tutorials and output files for students, and PowerPoint slides and test bank questions for instructors, make How to Use SPSS® the definitive, field-tested resource for learning SPSS. New to this edition: Fully updated to SPSS 24 and IBM SPSS Statistics Cloud New chapter on ANOVA New material on inter-rater reliability New material on syntax Additional coverage of data entry and management




Quasi-Experimentation


Book Description

Featuring engaging examples from diverse disciplines, this book explains how to use modern approaches to quasi-experimentation to derive credible estimates of treatment effects under the demanding constraints of field settings. Foremost expert Charles S. Reichardt provides an in-depth examination of the design and statistical analysis of pretest-posttest, nonequivalent groups, regression discontinuity, and interrupted time-series designs. He details their relative strengths and weaknesses and offers practical advice about their use. Reichardt compares quasi-experiments to randomized experiments and discusses when and why the former might be a better choice. Modern moethods for elaborating a research design to remove bias from estimates of treatment effects are described, as are tactics for dealing with missing data and noncompliance with treatment assignment. Throughout, mathematical equations are translated into words to enhance accessibility.




Doing Meta-Analysis with R


Book Description

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, dmetar, is introduced at the beginning of the guide. It contains data sets and several helper functions for the meta and metafor package used in the guide. The programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. Features • Contains two introductory chapters on how to set up an R environment and do basic imports/manipulations of meta-analysis data, including exercises • Describes statistical concepts clearly and concisely before applying them in R • Includes step-by-step guidance through the coding required to perform meta-analyses, and a companion R package for the book




The Routledge Reviewer’s Guide to Mixed Methods Analysis


Book Description

The Routledge Reviewer’s Guide to Mixed Methods Analysis is a groundbreaking edited book – the first devoted solely to mixed methods research analyses, or mixed analyses. Each of the 30 seminal chapters, authored by internationally renowned scholars, provides a simple and practical introduction to a method of mixed analysis. Each chapter demonstrates "how to conduct the analysis" in easy-to-understand language. Many of the chapters present new topics that have never been written before, and all chapters offer cutting-edge approaches to analysis. The book contains the following four sections: Part I Quantitative Approaches to Qualitative Data (e.g., factor analysis of text, multidimensional scaling of qualitative data); Part II Qualitative Approaches to Quantitative Data (e.g., qualitizing data, mixed methodological discourse analysis); Part III "Inherently" Mixed Analysis Approaches (e.g., qualitative comparative analysis, mixed methods social network analysis, social media analytics as mixed analysis, GIS as mixed analysis); and Part IV Use of Software for Mixed Data Analysis (e.g., QDA Miner, WordStat, MAXQDA, NVivo, SPSS). The audience for this book includes (a) researchers, evaluators, and practitioners who conduct a variety of research projects and who are interested in using innovative analyses that will allow them to extract more from their data; (b) academics, including faculty who would use this book in their scholarship, as well as in their graduate-level courses, and graduate students who need access to a comprehensive set of mixed analysis tools for their dissertations/theses and other research assignments and projects; and (c) computer-assisted data analysis software developers who are seeking additional mixed analyses to include within their software programs. Chapter 24 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.




Complex Surveys


Book Description

A complete guide to carrying out complex survey analysis using R As survey analysis continues to serve as a core component of sociological research, researchers are increasingly relying upon data gathered from complex surveys to carry out traditional analyses. Complex Surveys is a practical guide to the analysis of this kind of data using R, the freely available and downloadable statistical programming language. As creator of the specific survey package for R, the author provides the ultimate presentation of how to successfully use the software for analyzing data from complex surveys while also utilizing the most current data from health and social sciences studies to demonstrate the application of survey research methods in these fields. The book begins with coverage of basic tools and topics within survey analysis such as simple and stratified sampling, cluster sampling, linear regression, and categorical data regression. Subsequent chapters delve into more technical aspects of complex survey analysis, including post-stratification, two-phase sampling, missing data, and causal inference. Throughout the book, an emphasis is placed on graphics, regression modeling, and two-phase designs. In addition, the author supplies a unique discussion of epidemiological two-phase designs as well as probability-weighting for causal inference. All of the book's examples and figures are generated using R, and a related Web site provides the R code that allows readers to reproduce the presented content. Each chapter concludes with exercises that vary in level of complexity, and detailed appendices outline additional mathematical and computational descriptions to assist readers with comparing results from various software systems. Complex Surveys is an excellent book for courses on sampling and complex surveys at the upper-undergraduate and graduate levels. It is also a practical reference guide for applied statisticians and practitioners in the social and health sciences who use statistics in their everyday work.




Financial Statement Analysis


Book Description

Praise for Financial Statement Analysis A Practitioner's Guide Third Edition "This is an illuminating and insightful tour of financial statements, how they can be used to inform, how they can be used to mislead, and how they can be used to analyze the financial health of a company." -Professor Jay O. Light Harvard Business School "Financial Statement Analysis should be required reading for anyone who puts a dime to work in the securities markets or recommends that others do the same." -Jack L. Rivkin Executive Vice President (retired) Citigroup Investments "Fridson and Alvarez provide a valuable practical guide for understanding, interpreting, and critically assessing financial reports put out by firms. Their discussion of profits-'quality of earnings'-is particularly insightful given the recent spate of reporting problems encountered by firms. I highly recommend their book to anyone interested in getting behind the numbers as a means of predicting future profits and stock prices." -Paul Brown Chair-Department of Accounting Leonard N. Stern School of Business, NYU "Let this book assist in financial awareness and transparency and higher standards of reporting, and accountability to all stakeholders." -Patricia A. Small Treasurer Emeritus, University of California Partner, KCM Investment Advisors "This book is a polished gem covering the analysis of financial statements. It is thorough, skeptical and extremely practical in its review." -Daniel J. Fuss Vice Chairman Loomis, Sayles & Company, LP




The Britannica Guide to Analysis and Calculus


Book Description

Examines the history of analysis and calculus, including the geniuses of invention and theory, the practical applications of the math, and explanations of the major topics.




Guide to Analysing Companies


Book Description

In today's volatile, complex and fast-moving business world, it can be difficult to gauge how sound a company really is. An apparently strong balance sheet and impressive reported profits may be hiding all sorts of problems that could even spell bankruptcy. So how do you: Know whether a company is well run and doing well? Decide which ratios and benchmarks to use to assess performance? Work out if a company has massaged its results? Recognize the danger signs on the corporate horizon? Compare companies operating in different sectors or countries? These and many other important questions are answered in a completely updated and revised sixth edition of this clear and comprehensive guide. It is aimed at anyone who wants to understand a company's annual report, judge a customer's creditworthiness, assess a company's investment potential, and much more.