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Quantitative Research using R de Smruti Bulsari

Quantitative Research using R

Autor Smruti Bulsari, Kiran Pandya
en Limba Engleză Hardback – 17 mar 2026

Prin volumul Quantitative Research using R, autorii Smruti Bulsari și Kiran Pandya propun o sinteză metodologică necesară în peisajul academic actual, unde alfabetizarea digitală în analiza datelor a devenit obligatorie. Ceea ce aduce nou această lucrare este modul hibrid în care tratează cercetarea cantitativă: nu se limitează la a fi un manual de statistică teoretică, ci funcționează ca un ghid procedural complet, ancorând fiecare concept matematic în execuția practică din mediul RStudio.

Apreciem în mod deosebit progresia logică a materialului. De la fundamentarea conceptelor de eșantionare și erori de selecție în primele capitole, textul evoluează natural către teste de ipoteze și regresii, culminând cu tehnici avansate precum analiza de senzitivitate și analiza multi-răspuns. Această structură în 21 de capitole permite cititorului să utilizeze volumul atât ca suport de curs, cât și ca manual de referință pentru proiecte de cercetare specifice. Integrarea a 156 de ilustrații și diagrame facilitează înțelegerea output-urilor complexe, eliminând „cutia neagră” a codului programat.

Ca alternativă la Using R for Data Analysis in Social Sciences de Quan Li pentru cursurile de metodologie, lucrarea de față are avantajul unei acoperiri mult mai vaste a metodelor multivariate (cluster, factori, MDS), depășind abordarea minimalistă a altor texte introductive. În comparație cu Quantitative Methods for the Social Sciences de Daniel Stockemer, care se concentrează masiv pe designul sondajelor, volumul publicat de Routledge pune un accent mai puternic pe interpretarea statistică riguroasă și pe diversitatea modelelor de regresie (Logit, Probit, ANCOVA). Este un instrument robust pentru economiști, psihologi și specialiști în științe sociale care au nevoie de precizie în interpretarea datelor transversale.

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Specificații

ISBN-13: 9781032702827
ISBN-10: 1032702826
Pagini: 372
Ilustrații: 156
Dimensiuni: 174 x 246 mm
Greutate: 0.85 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Locul publicării:Oxford, United Kingdom

Public țintă

Postgraduate, Professional Reference, Undergraduate Advanced, and Undergraduate Core

De ce să citești această carte

Recomandăm această carte studenților și cercetătorilor din științe sociale care doresc să facă tranziția de la analiza teoretică la cea aplicată în R. Veți câștiga nu doar competențe de programare, ci și capacitatea de a interpreta critic rezultatele statistice. Este un resursă esențială pentru cei care au nevoie de o metodologie clară pentru teze de doctorat sau studii clinice, acoperind de la vizualizarea datelor până la analize multivariate complexe.

Despre autor

Smruti Bulsari și Kiran Pandya sunt academicieni cu o vastă experiență în metodologii cantitative aplicate. În timp ce lucrările lor anterioare, precum Public Health and Menstrual Hygiene Practices in India, s-au concentrat pe aplicarea metodelor statistice pentru a evidenția inechitățile socio-economice și costurile de igienă, prin Quantitative Research using R aceștia își formalizează expertiza pedagogică. Autorii reușesc să traducă rigoarea cercetării de teren într-un format didactic, facilitând accesul cercetătorilor la instrumente software open-source pentru analiza datelor complexe.

Cuprins

Foreword  Preface  1. Introduction to R and RStudio  2. Understanding Quantitative Data  3. Sample Size and Sample Selection Bias  4. Data Structures and Wrangling  5. Data Visualisation  6. Hypothesis Testing  7. Descriptive Statistics  8. t-Tests: One-Sample, Independent Samples and Paired Samples  9. Analysis of Variance  10. Correlation Analysis  11. Regression Analysis  12. Analysis of Covariance (ANCOVA)  13. Logistic Regression (Logit) and Probit Models  14. Discriminant Analysis  15. Non-Parametric Tests  16. Factor Analysis: Principal Components Method  17. Cluster Analysis  18. Multidimensional Scaling  19. Sensitivity Analysis  20. Survival Analysis  21. Multiresponse Analysis    Appendix – A: Description of Datasets used in this book

Recenzii

This book is an excellent resource for anyone working with R. It combines clear explanations with practical examples, making even complex concepts easy to grasp. Whether you are new to R or looking to deepen your skills, you will find this book both accessible and highly valuable. I strongly recommend it to students, researchers, and professionals who want to make the most of R in their work.
Magdalena Wallbaum, Research Fellow, Care Policy and Evaluation Centre (CPEC), London School of Economics and Political Science, United Kingdom
This book offers a clear and comprehensive overview to quantitative methods using R, beginning with an introduction to the programming language and data handling, to then progress to statistical analysis. The book successfully complements the theory with practical implementations and their respective analyses. This balance makes it a great resource for graduate students, academics who might consider it as a textbook, as well as practitioners such as data scientists and quantitative researchers.
Dr Felipe Maldonado, Assistant Professor, School of Mathematics, Statistics and Actuarial Science, University of Essex, United Kingdom
Even in the age of AI-generated codes, the research community needs a trusted and experienced guide. Also, 90% of research involves doing the basics right. Dr Pandya and Dr Bulsari's new book on R analysis offers such guide on the basics and much more. Health economists among the readers would find chapter 20 on survival analysis and chapter 16 on factor analysis particularly useful for decision modelling and multidimensional health outcomes research.
Joseph Kwon, Senior Researcher in Health Economics, NIHR ARC Dementia Research Fellow, Mental Health Mission NICE Lead, Nuffield Department of Primary Care and Health Services, University of Oxford, United Kingdom
An excellent and comprehensive text that demystifies quantitative methods using R. With its wide coverage from foundational concepts to sophisticated statistical techniques it is a must-have for anyone engaged in research.
Pallavi Banerjee, Assistant Professor, Faculty of Education, University of Cambridge, United Kingdom
This new book on R for Quantitative Research is a must-read for both beginners and advanced researchers in the social sciences. It offers a clear and accessible introduction to R, seamlessly guiding readers into the world of statistical analysis. Covering essential topics with depth and clarity, it equips users with the tools and knowledge needed to tackle data analysis confidently, making it an invaluable resource for anyone looking to master statistics with R.
Gaurang Rami, Professor in Economics, and Head, Department of Economics, Veer Narmad South Gujarat University, Surat, India
R for Quantitative Researchers offers an extremely comprehensive walk through of all aspects of R and R Studio for researchers new to quantitative software as well as those much more established. The use of appropriate examples offers the reader opportunities to interactively engage with the book and advance their knowledge and understanding. It has been incredibly helpful in my professional development as a quantitative researcher.
Ben Gould, Senior Research Officer, Institute of Public Health and Wellbeing, University of Essex, United Kingdom
This book is an essential guide for researchers in economics and the social sciences, offering an ideal mix of statistical theory with practical R applications. The chapters on multivariate analysis and non-parametric statistics are particularly valuable, providing the tools to analyse complex, real-world social data that often challenges traditional methods.
Samar Ajeeb, Assistant Professor in Economics and Project Management, Taif University, Saudi Arabia

Descriere scurtă

The book is a unique blend of quantitative research and statistical analysis using R. Lucidly written, it covers a range of statistical techniques applicable to cross-sectional data in the backdrop of quantitative research and survey research. In addition to the basic concepts, this book also explores advanced multivariate statistics topics like principal components analysis, cluster analysis, multidimensional scaling and more.
This volume begins with an introduction to R, RStudio and gives a step-by-step approach to installation and usage. The chapters on quantitative data and sampling build the background for understanding quantitative and survey research. It gradually builds the foundations into descriptive and inferential statistics, while simultaneously providing and describing the R code as well as the interpretation of the output generated by executing that R code. This gives the reader clarity in both the techniques as well as the R code. Many examples relevant to different statistical analyses make the book interesting to readers across different disciplines.
The book will be useful to the students, researchers and teachers of Economics, Psychology, Management, Data Science, Education, and other social science disciplines. Students at undergraduate and graduate level, doctoral, post-doctoral and professional researchers, as well as teachers of research methodology and quantitative techniques will find this book a handy resource for using R for quantitative research.

Notă biografică

Smruti Bulsari is currently a Researcher at the Nuffield Department of Primary Care and Health Sciences, University of Oxford, prior to which she was with the University of Essex. She holds a PhD in Economics and Master’s degrees in Economics and Data Science. She has a wide experience of working with large datasets and different statistical software. She makes extensive use of R for quantitative analysis as well as developing simulation models in health economics. She has a wide experience of teaching and research; she has worked on research projects funded by NIHR, ESRC, British Academy, ICSSR and the Government of Gujarat.
Kiran Pandya is currently the Provost of Sarvajanik University. He has more than 40 years of teaching, research and administrative experience, out of which he was the Professor and Head in the Department of Human Resource Development, Veer Narmad South Gujarat University, Surat (Gujarat, India) for close to 16 years. He has conducted a large number of training programmes and workshops in quantitative techniques using different software, for researchers and academics. Kiran holds the degree of Doctor of Philosophy in Economics from the University of Sussex, for which he was awarded the Academic Staff Scholarship by the Commonwealth Commission in the UK.