When you want to find research design and statistical analysis, you may need to consider between many choices. Finding the best research design and statistical analysis is not an easy task. In this post, we create a very short list about top 9 the best research design and statistical analysis for you. You can check detail product features, product specifications and also our voting for each product. Let’s start with following top 9 research design and statistical analysis:
Best research design and statistical analysis
1. Quantitative and Statistical Research Methods: From Hypothesis to Results
Description
Quantitative and Statistical Research Methods
This user-friendly textbook teaches students to understand and apply procedural steps in completing quantitative studies. It explains statistics while progressing through the steps of the hypothesis-testing process from hypothesis to results. The research problems used in the book reflect statistical applications related to interesting and important topics. In addition, the book provides a Research Analysis and Interpretation Guide to help students analyze research articles.
Designed as a hands-on resource, each chapter covers a single research problem and offers directions for implementing the research method from start to finish. Readers will learn how to:
- Pinpoint research questions and hypotheses
- Identify, classify, and operationally define the study variables
- Choose appropriate research designs
- Conduct power analysis
- Select an appropriate statistic for the problem
- Use a data set
- Conduct data screening and analyses using SPSS
- Interpret the statistics
- Write the results related to the problem
Quantitative and Statistical Research Methods allows students to immediately, independently, and successfully apply quantitative methods to their own research projects.
2. Research Design and Statistical Analysis: Third Edition
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Used Book in Good ConditionDescription
Research Design and Statistical Analysis provides comprehensive coverage of the design principles and statistical concepts necessary to make sense of real data. The books goal is to provide a strong conceptual foundation to enable readers to generalize concepts to new research situations. Emphasis is placed on the underlying logic and assumptions of the analysis and what it tells the researcher, the limitations of the analysis, and the consequences of violating assumptions. Sampling, design efficiency, and statistical models are emphasized throughout. As per APA recommendations, emphasis is also placed on data exploration, effect size measures, confidence intervals, and using power analyses to determine sample size. "Real-world" data sets are used to illustrate data exploration, analysis, and interpretation. The book offers a rare blend of the underlying statistical assumptions, the consequences of their violations, and practical advice on dealing with them.
Changes in the New Edition:
- Each section of the book concludes with a chapter that provides an integrated example of how to apply the concepts and procedures covered in the chapters of the section. In addition, the advantages and disadvantages of alternative designs are discussed.
- A new chapter (1) reviews the major steps in planning and executing a study, and the implications of those decisions for subsequent analyses and interpretations.
- A new chapter (13) compares experimental designs to reinforce the connection between design and analysis and to help readers achieve the most efficient research study.
- A new chapter (27) on common errors in data analysis and interpretation.
- Increased emphasis on power analyses to determine sample size using the G*Power 3 program.
- Many new data sets and problems.
- More examples of the use of SPSS (PASW) Version 17, although the analyses exemplified are readily carried out by any of the major statistical software packages.
- A companion website with the data used in the text and the exercises in SPSS and Excel formats; SPSS syntax files for performing analyses; extra material on logistic and multiple regression; technical notes that develop some of the formulas; and a solutions manual and the text figures and tables for instructors only.
Part 1 reviews research planning, data exploration, and basic concepts in statistics including sampling, hypothesis testing, measures of effect size, estimators, and confidence intervals. Part 2 presents between-subject designs. The statistical models underlying the analysis of variance for these designs are emphasized, along with the role of expected mean squares in estimating effects of variables, the interpretation of nteractions, and procedures for testing contrasts and controlling error rates. Part 3 focuses on repeated-measures designs and considers the advantages and disadvantages of different mixed designs. Part 4 presents detailed coverage of correlation and bivariate and multiple regression with emphasis on interpretation and common errors, and discusses the usefulness and limitations of these procedures as tools for prediction and for developing theory.
This is one of the few books with coverage sufficient for a 2-semester course sequence in experimental design and statistics as taught in psychology, education, and other behavioral, social, and health sciences. Incorporating the analyses of both experimental and observational data provides continuity of concepts and notation. Prerequisites include courses on basic research methods and statistics. The book is also an excellent resource for practicing researchers.
3. Study Design and Statistical Analysis: A Practical Guide for Clinicians
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Used Book in Good ConditionDescription
This book takes the reader through the entire research process: choosing a question, designing a study, collecting the data, using univariate, bivariate and multivariable analysis, and publishing the results. It does so by using plain language rather than complex derivations and mathematical formulas. It focuses on the nuts and bolts of performing research by asking and answering the most basic questions about doing research studies. Making good use of numerous tables, graphs and tips, this book helps to demystify the process. A generous number of up-to-date examples from the clinical literature give an illustrated and practical account of how to use multivariable analysis.4. Epidemiology: Study Design and Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
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For all our books; Cargo will be delivered in the required time. 100% Satisfaction is Guaranteed!Description
Highly praised for its broad, practical coverage, the second edition of this popular text incorporated the major statistical models and issues relevant to epidemiological studies. Epidemiology: Study Design and Data Analysis, Third Edition continues to focus on the quantitative aspects of epidemiological research. Updated and expanded, this edition shows students how statistical principles and techniques can help solve epidemiological problems.
New to the Third Edition
- New chapter on risk scores and clinical decision rules
- New chapter on computer-intensive methods, including the bootstrap, permutation tests, and missing value imputation
- New sections on binomial regression models, competing risk, information criteria, propensity scoring, and splines
- Many more exercises and examples using both Stata and SAS
- More than 60 new figures
After introducing study design and reviewing all the standard methods, this self-contained book takes students through analytical methods for both general and specific epidemiological study designs, including cohort, case-control, and intervention studies. In addition to classical methods, it now covers modern methods that exploit the enormous power of contemporary computers. The book also addresses the problem of determining the appropriate size for a study, discusses statistical modeling in epidemiology, covers methods for comparing and summarizing the evidence from several studies, and explains how to use statistical models in risk forecasting and assessing new biomarkers. The author illustrates the techniques with numerous real-world examples and interprets results in a practical way. He also includes an extensive list of references for further reading along with exercises to reinforce understanding.
Web Resource
A wealth of supporting material can be downloaded from the books CRC Press web page, including:
- Real-life data sets used in the text
- SAS and Stata programs used for examples in the text
- SAS and Stata programs for special techniques covered
- Sample size spreadsheet
5. An EasyGuide to Research Design & SPSS (EasyGuide Series)
Description
An EasyGuide to Research Design and SPSS is an essential resource for students to successfully navigate and complete research projects. Using a clear, concise, and conversational writing style, authors Beth M. Schwartz, Janie H. Wilson, and Dennis M. Goff cover all of the most basic and common designs and analyses that students need to know for appropriately testing a hypothesis. The handbook includes step-by-step instructions accompanied by ample screenshots for working with data in SPSS, along with guidance on interpreting outputs and formatting results in APA style. The Second Edition features a streamlined organization, updated references, and new content on factorial designs, effect size, and G*Power.6. Design, Evaluation, and Analysis of Questionnaires for Survey Research (Wiley Series in Survey Methodology)
Description
Praise for theFirst Edition
...this book is quite inspiring, giving many practical ideas for survey research, especially for designing better questionnaires.
International Statistical Review
Reflecting modern developments in the field of survey research, the Second Edition of Design, Evaluation, and Analysis of Questionnaires for Survey Research continues to provide cutting-edge analysis of the important decisions researchers make throughout the survey design process.
The new edition covers the essential methodologies and statistical tools utilized to create reliable and accurate survey questionnaires, which unveils the relationship between individual question characteristics and overall question quality. Since the First Edition, the computer program Survey Quality Prediction (SQP) has been updated to include new predictions of the quality of survey questions on the basis of analyses of Multi-Trait Multi-Method experiments. The improved program contains over 60,000 questions, with translations in most European languages. Featuring an expanded explanation of the usage and limitations of SQP 2.0, the Second Edition also includes:
New practice problems to provide readers with real-world experience in survey research and questionnaire design
A comprehensive outline of the steps for creating and testing survey questionnaires
Contemporary examples that demonstrate the many pitfalls of questionnaire design and ways to avoid similar decisions
Design, Evaluation, and Analysis of Questionnaires for Survey Research, Second Edition is an excellent textbook for upper-undergraduate and graduate-level courses in methodology and research questionnaire planning, as well as an ideal resource for social scientists or survey researchers needing to design, evaluate, and analyze questionnaires.
7. Applied Multivariate Research: Design and Interpretation
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SAGE Publications IncDescription
Using a conceptual, non-mathematical approach, the updated Third Edition of Applied Multivariate Research: Design and Interpretation provides full coverage of the wide range of multivariate topics that graduate students across the social and behavioral sciences encounter. Authors Lawrence S. Meyers, Glenn Gamst, and A. J. Guarino integrate innovative multicultural topics in examples throughout the book, which include both conceptual and practical coverage of: statistical techniques of data screening; multiple regression; multilevel modeling; exploratory factor analysis; discriminant analysis; structural equation modeling; structural equation modeling invariance; survival analysis; multidimensional scaling; and cluster analysis.8. Social Science Research Design and Statistics: A Practitioner's Guide to Research Methods and IBM SPSS Analysis
Description
This book integrates social science research methods and the descriptions of over 40 univariate, bivariate, and multivariate tests to include a description of the purpose, key assumptions and requirements, example research question and null hypothesis, SPSS procedures, display and interpretation of SPSS output, and what to report for each test. It is classroom tested and current with IBM SPSS 22. Additionally, a companion website provides book users with supplemental resources to include SPSS data files linked to the test examples presented in this book.9. The Model Thinker: What You Need to Know to Make Data Work for You
Description
From the stock market to genomics laboratories, census figures to marketing email blasts, we are awash with data. But as anyone who has ever opened up a spreadsheet packed with seemingly infinite lines of data knows, numbers aren't enough: we need to know how to make those numbers talk. In The Model Thinker, social scientist Scott E. Page shows us the mathematical, statistical, and computational models--from linear regression to random walks and far beyond--that can turn anyone into a genius. At the core of the book is Page's "many-model paradigm," which shows the reader how to apply multiple models to organize the data, leading to wiser choices, more accurate predictions, and more robust designs. The Model Thinker provides a toolkit for business people, students, scientists, pollsters, and bloggers to make them better, clearer thinkers, able to leverage data and information to their advantage.
