examples of quantitative research in humanities and social sciences pdf

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Collection  02 October 2018

Quantitative methodologies: novel applications in the humanities and social sciences

At a time when data analysis is increasingly driving research and decision-making, computational analysis, statistical models, computer-based programmes, and other quantitative methods have never been more important. From the interrogation of empirical questions about cultural, social, and behavioural phenomena, to the formation of evidence-based policy, the application of quantitative methods in making sense of real-world data is of paramount importance across all fields of academic enquiry.

Whilst the use of quantitative methodologies is more established in the social sciences, we recognise their growing application in many areas of the humanities. As such, we encourage the submission of novel research arising in such areas where the usefulness of such quantitative approaches is gaining increased recognition.

Original research is invited that:

• Presents the application of either established or new statistical, computational, and other quantitative methodologies/methods;
• Discusses real systems represented by appropriate datasets;
• Includes a detailed explanation of the application of method in the relevant area of study;
• Discusses and interprets findings in context of appropriate wider literature;
• Demonstrates a clear significance and contribution to advancing knowledge in the area of application.

Review articles are also welcomed that synthesise recent and emerging developments pertaining to the application of methodological approaches in the humanities or social sciences.

Research reporting the application of methods in all areas of the humanities and social sciences is welcomed including, but not restricted to, the following fields:

Sebastian Ahnert

King's College, UK; University of Cambridge, UK

Juyong Park

Korea Advanced Institute of Science & Technology, Korea

Maximilian Schich

The University of Texas at Dallas, USA

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A fragment-based approach for computing the long-term visual evolution of historical maps

• Remi Petitpierre
• Johannes H. Uhl
• Frédéric Kaplan

Analysis of the agricultural economic value of a weather forecasting service based on a survey of peasant households in Chinese provinces

• Xiaofeng Zhao
• Chunxiang Leng

Unraveling the dynamics and identifying the “superstars” of R&D alliances in IUR collaboration: a two-mode network analysis in China

Welfare regimes in Asia: convergent or divergent?

• Seungwoo Han

Assessing the effectiveness of targeted poverty alleviation policies in Xinjiang, China

• Yujie Huang
• Xianke Huang

“Bringing in” and “Going abroad”: A bibliometric evaluation of the internationalization of archaeology in Mainland China

Releasing survey microdata with exact cluster locations and additional privacy safeguards

• Alejandra Arias-Salazar
• Timo Schmid

Network analysis reveals insights about the interconnections of Judaism and Christianity in the first centuries CE

• Michal Bar-Asher Siegal
• Yossi Yovel

A decomposition of book structure through ousiometric fluctuations in cumulative word-time

• Mikaela Irene Fudolig
• Thayer Alshaabi
• Peter Sheridan Dodds

An algorithm for predicting job vacancies using online job postings in Australia

• David Evans
• Claire Mason
• Andrew Reeson

Dynamic value sharing based on employee contribution as a competitiveness-enhancing device

• Zuomiao Xie
• Alistair Palferman

Household behavior and vulnerability to acute malnutrition in Kenya

• Ravi Bhavnani
• Nina Schlager
• Tirtha Patel

Syntactic complexity in legal translated texts and the use of plain English: a corpus-based study

• Xiaowen Lin
• Muhammad Afzaal
• Hessah Saleh Aldayel

Empirical evidence of the impact of mobility on property crimes during the first two waves of the COVID-19 pandemic

• Kandaswamy Paramasivan
• Rahul Subburaj
• Nandan Sudarsanam

Scientific authorship by gender: trends before and during a global pandemic

• Ji-Young Son
• Michelle L. Bell

Modeling narrative features in TV series: coding and clustering analysis

• Marta Rocchi
• Guglielmo Pescatore

Varying climatic-social-geographical patterns shape the conflict risk at regional and global scales

• Mengmeng Hao
• Fangyu Ding

Cultural Divergence in popular music: the increasing diversity of music consumption on Spotify across countries

• Pablo Bello
• David Garcia

Humour and sarcasm: expressions of global warming on Twitter

• Hande Eslen-Ziya

Embodiment of concealable stigma disclosure through dynamics of movement and language

• Hannah M. Douglas
• Stacie Furst-Holloway
• Rachel W. Kallen

The language of happiness in self-reported descriptions of happy moments: Words, concepts, and entities

• Antonio Moreno-Ortiz
• Chantal Pérez-Hernández
• María García-Gámez

You trust a face like yours

• Tamami Nakano
• Takuto Yamamoto

Winners and runners-up alike?—a comparison between awardees and special mention recipients of the most reputable science award in Colombia via a composite citation indicator

• Julián D. Cortés
• Daniel A. Andrade

A social networks-driven approach to understand the unique alcohol mixing patterns of tuberculosis patients: reporting methods and findings from a high TB-burden setting

• Karikalan Nagarajan
• Bharathidasan Palani
• Malaisamy Muniyandi

Organizational cultural strength as the negative cross-entropy of mindshare: a measure based on descriptive text

• Arianna Marchetti
• Phanish Puranam

How architectural principles can help conceptualize and analyze breakups among intergenerational households

• Peter D. Brandon
• Danielle George-Lucas
• Oleg Ivashchenko

Facial recognition as a tool to identify Roman emperors: towards a new methodology

• Darshan Srirangachar Ramesh
• Sam Heijnen
• Florens de Wit

Emergence of protests during the COVID-19 pandemic: quantitative models to explore the contributions of societal conditions

• Koen van der Zwet
• Ana I. Barros
• Peter M. A. Sloot

Gravity models do not explain, and cannot predict, international migration dynamics

• Robert M. Beyer
• Jacob Schewe
• Hermann Lotze-Campen

Polarization, abstention, and the median voter theorem

• Matthew I. Jones
• Antonio D. Sirianni

The impact of casino proximity on northeast urban communities: a literature review

• Paulette J. O’Gilvie

Does the growth of military hard power back up the growth of monetary soft power via data-driven probabilistic optimal relations?

• Ray-Ming Chen

Spatial stratification and socio-spatial inequalities: the case of Seoul and Busan in South Korea

Identifying the roots of inequality of opportunity in South Korea by application of algorithmic approaches

Understanding the timing of chinese border incursions into india.

• Kevin T. Greene
• Caroline Tornquist
• V. S. Subrahmanian

Dynamics of artistic style: a computational analysis of the Maker’s motoric qualities in a clay-relief practice

• Ayala Prusak
• Amit Raphael Zoran

Computational appraisal of gender representativeness in popular movies

• Antoine Mazières
• Telmo Menezes
• Camille Roth

The fractal dimension of Islamic and Persian four-folding gardens

• Agnès Patuano
• M. Francisca Lima

Health shocks and vulnerability to poverty in Congo

• Séverin Aimé Blanchard Ouadika

On how religions could accidentally incite lies and violence: folktales as a cultural transmitter

• Quan-Hoang Vuong
• Manh-Tung Ho
• Viet-Phuong La

Crime and its fear in social media

• Rafael Prieto Curiel
• Stefano Cresci
• Steven Richard Bishop

What do we know about poverty in North Korea?

• Jesús Crespo Cuaresma
• Olha Danylo
• Juan Carlos Laso Bayas

Development of a scale of Chinese primary school teachers’ job embeddedness

• Xuguang Sun
• Ailing Huang

Statistical reliability analysis for a most dangerous occupation: Roman emperor

• Joseph Homer Saleh

Assessing potential landscape service trade-offs driven by urbanization in Switzerland

• Madleina Gerecke
• Oskar Hagen
• Loïc Pellissier

Quantification of textual comprehension difficulty with an information theory-based algorithm

• Louise Bogéa Ribeiro
• Anderson Raiol Rodrigues
• Manoel da Silva Filho

Emergence of complexity in poetry: “Soleils couchants” by Verlaine

• In-Ryeong Choi

Early prediction of the outcome of Kickstarter campaigns: is the success due to virality?

• Alex Kindler
• Michael Golosovsky
• Sorin Solomon

Interest rates forecasting and stress testing in India: a PCA-ARIMA approach

• Aswani Kumar Mallick
• Alok Kumar Mishra

Diversity of inference strategies can enhance the ‘wisdom-of-crowds’ effect

• Itsuki Fujisaki
• Hidehito Honda
• Kazuhiro Ueda

The possibility and desirability of replication in the humanities

Buildup of speaking skills in an online learning community: a network-analytic exploration

• Rasoul Shafipour
• Raiyan Abdul Baten
• Mohammed Ehsan Hoque

Coherent oscillations in word-use data from 1700 to 2008

• Marcelo A Montemurro
• Damián H Zanette

Race, religion and the city: twitter word frequency patterns reveal dominant demographic dimensions in the United States

• Eszter Bokányi
• Dániel Kondor
• Gábor Vattay

Hierarchical networks of scientific journals

• Gergely Palla
• Gergely Tibély
• Tamás Vicsek

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The SAGE Handbook of Quantitative Methodology for the Social Sciences

• David Kaplan - University of Wisconsin - Madison, USA
• Description

Click 'Additional Materials' for downloadable samples "The 24 chapters in this Handbook span a wide range of topics, presenting the latest quantitative developments in scaling theory, measurement, categorical data analysis, multilevel models, latent variable models, and foundational issues. Each chapter reviews the historical context for the topic and then describes current work, including illustrative examples where appropriate. The level of presentation throughout the book is detailed enough to convey genuine understanding without overwhelming the reader with technical material. Ample references are given for readers who wish to pursue topics in more detail. The book will appeal to both researchers who wish to update their knowledge of specific quantitative methods, and students who wish to have an integrated survey of state-of- the-art quantitative methods." —Roger E. Millsap, Arizona State University "This handbook discusses important methodological tools and topics in quantitative methodology in easy to understand language. It is an exhaustive review of past and recent advances in each topic combined with a detailed discussion of examples and graphical illustrations. It will be an essential reference for social science researchers as an introduction to methods and quantitative concepts of great use." —Irini Moustaki, London School of Economics, U.K.

"David Kaplan and SAGE Publications are to be congratulated on the development of a new handbook on quantitative methods for the social sciences. The Handbook is more than a set of methodologies, it is a journey. This methodological journey allows the reader to experience scaling, tests and measurement, and statistical methodologies applied to categorical, multilevel, and latent variables. The journey concludes with a number of philosophical issues of interest to researchers in the social sciences. The new Handbook is a must purchase." —Neil H. Timm, University of Pittsburgh The SAGE Handbook of Quantitative Methodology for the Social Sciences is the definitive reference for teachers, students, and researchers of quantitative methods in the social sciences, as it provides a comprehensive overview of the major techniques used in the field. The contributors, top methodologists and researchers, have written about their areas of expertise in ways that convey the utility of their respective techniques, but, where appropriate, they also offer a fair critique of these techniques. Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.

The handbook is divided into six sections:

• Scaling • Testing and Measurement • Models for Categorical Data • Models for Multilevel Data • Models for Latent Variables • Foundational Issues

These sections, comprising twenty-four chapters, address topics in scaling and measurement, advances in statistical modeling methodologies, and broad philosophical themes and foundational issues that transcend many of the quantitative methodologies covered in the book.

The Handbook is indispensable to the teaching, study, and research of quantitative methods and will enable readers to develop a level of understanding of statistical techniques commensurate with the most recent, state-of-the-art, theoretical developments in the field. It provides the foundations for quantitative research, with cutting-edge insights on the effectiveness of each method, depending on the data and distinct research situation.

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email [email protected] . Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html .

For assistance with your order: Please email us at [email protected] or connect with your SAGE representative.

SAGE 2455 Teller Road Thousand Oaks, CA 91320 www.sagepub.com

“The 24 chapters in this Handbook span a wide range of topics, presenting the latest quantitative developments in scaling theory, measurement, categorical data analysis, multilevel models, latent variable models, and foundational issues. Each chapter reviews the historical context for the topic and then describes current work, including illustrative examples where appropriate. The level of presentation throughout the book is detailed enough to convey genuine understanding without overwhelming the reader with technical material. Ample references are given for readers who wish to pursue topics in more detail. The book will appeal to both researchers who wish to update their knowledge of specific quantitative methods, and students who wish to have an integrated survey of state-of- the-art quantitative methods.”

“This handbook discusses important methodological tools and topics in quantitative methodology in easy to understand language. It is an exhaustive review of past and recent advances in each topic combined with a detailed discussion of examples and graphical illustrations. It will be an essential reference for social science researchers as an introduction to methods and quantitative concepts of great use.”

“David Kaplan and SAGE Publications are to be congratulated on the development of a new handbook on quantitative methods for the social sciences. The Handbook is more than a set of methodologies, it is a journey. This methodological journey allows the reader to experience scaling, tests and measurement, and statistical methodologies applied to categorical, multilevel, and latent variables. The journey concludes with a number of philosophical issues of interest to researchers in the social sciences. The new Handbook is a must purchase.”

"David Kaplan has convened a panel of top-notch methodologians, who take on the challenge in the writing of The SAGE Handbook of Quantitative Methodology for the Social Sciences (SHQM). The result is an engrossing collection of chapters that are sure to add screwdrivers, wrenches, and the occasional buzzsaw to your toolbox. A notable strength of the SHQM is the generally structure of each chapter. The chapters of the SHQM are a worthy accomplishment. The SHQM is both well conceived and well executed, providing the reader with numerous insights and a broader sense for the available tools of the quantitative methodological trade. It is most likely that few readers will have the opportunity to read this book from cover to cover, but should they feel so inspired, they will find the effort both rewarding and thought provoking."

"The Handbook provides an excellent introduction to broad range of state-of-the-art quantitative methods applicable to the social sciences. It shows the breadth and depth of advanced quantitative methods used by social scientists from numerous interrelated disciplines, it is rich with examples of real-world applications of these methods, and it provides suggestions for further readings and study in these areas. It is well worth reading cover-to-cover, and it is a very useful addition to the reference libraries of all quantitative social scientists, applied statisticians, and graduate students."

• Provides a comprehensive overview of the major techniques used in the field.
• Top methodologists and researchers have written about their areas of expertise
• Relevance to real-world problems in the social sciences is an essential ingredient of each chapter and makes this an invaluable resource.
• Indispensable to the teaching, study, and research of quantitative methods.
• Provides the foundations for quantitative research, with cutting-edge insights on the effectiveness of each method.

Sample Materials & Chapters

Chapter 1. Dual Scaling

Chapter 3. Principal Components Analysis with Nonlinear Optimal Scaling Transfo

Chapter 5. Test Modeling

Select a Purchasing Option

This title is also available on SAGE Knowledge , the ultimate social sciences online library. If your library doesn’t have access, ask your librarian to start a trial .

This title is also available on SAGE Research Methods , the ultimate digital methods library. If your library doesn’t have access, ask your librarian to start a trial .

Book series

Quantitative Methods in the Humanities and Social Sciences

About this book series.

• Thomas DeFanti,
• Anthony Grafton,
• Thomas E. Levy,
• Lev Manovich,
• Alyn Rockwood

Book titles in this series

A quantitative portrait of analytic philosophy.

Looking Through the Margins

• Eugenio Petrovich
• Copyright: 2024

Available Renditions

Database Computing for Scholarly Research

Case Studies Using the Online Cultural and Historical Research Environment

• Sandra R. Schloen
• Miller C. Prosser
• Copyright: 2023

Who Wrote Citizen Kane?

Statistical Analysis of Disputed Co-Authorship

• Warren Buckland

Capturing the Senses

Digital Methods for Sensory Archaeologies

• Giacomo Landeschi
• Eleanor Betts
• Open Access

Let’s Calculate Bach

Applying Information Theory and Statistics to Numbers in Music

• Alan Shepherd
• Copyright: 2021

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A Quick Guide to Quantitative Research in the Social Sciences

(11 reviews)

Christine Davies, Carmarthen, Wales

Copyright Year: 2020

Last Update: 2021

Publisher: University of Wales Trinity Saint David

Language: English

Formats Available

Conditions of use.

Learn more about reviews.

Reviewed by Tiffany Kindratt, Assistant Professor, University of Texas at Arlington on 3/9/24

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers... read more

Comprehensiveness rating: 3 see less

The text provides a brief overview of quantitative research topics that is geared towards research in the fields of education, sociology, business, and nursing. The author acknowledges that the textbook is not a comprehensive resource but offers references to other resources that can be used to deepen the knowledge. The text does not include a glossary or index. The references in the figures for each chapter are not included in the reference section. It would be helpful to include those.

Content Accuracy rating: 4

Overall, the text is accurate. For example, Figure 1 on page 6 provides a clear overview of the research process. It includes general definitions of primary and secondary research. It would be helpful to include more details to explain some of the examples before they are presented. For instance, the example on page 5 was unclear how it pertains to the literature review section.

Relevance/Longevity rating: 4

In general, the text is relevant and up-to-date. The text includes many inferences of moving from qualitative to quantitative analysis. This was surprising to me as a quantitative researcher. The author mentions that moving from a qualitative to quantitative approach should only be done when needed. As a predominantly quantitative researcher, I would not advice those interested in transitioning to using a qualitative approach that qualitative research would enhance their research—not something that should only be done if you have to.

Clarity rating: 4

The text is written in a clear manner. It would be helpful to the reader if there was a description of the tables and figures in the text before they are presented.

Consistency rating: 4

The framework for each chapter and terminology used are consistent.

Modularity rating: 4

The text is clearly divided into sections within each chapter. Overall, the chapters are a similar brief length except for the chapter on data analysis, which is much more comprehensive than others.

Organization/Structure/Flow rating: 4

The topics in the text are presented in a clear and logical order. The order of the text follows the conventional research methodology in social sciences.

Interface rating: 5

I did not encounter any interface issues when reviewing this text. All links worked and there were no distortions of the images or charts that may confuse the reader.

Grammatical Errors rating: 3

There are some grammatical/typographical errors throughout. Of note, for Section 5 in the table of contents. “The” should be capitalized to start the title. In the title for Table 3, the “t” in typical should be capitalized.

Cultural Relevance rating: 4

The examples are culturally relevant. The text is geared towards learners in the UK, but examples are relevant for use in other countries (i.e., United States). I did not see any examples that may be considered culturally insensitive or offensive in any way.

I teach a course on research methods in a Bachelor of Science in Public Health program. I would consider using some of the text, particularly in the analysis chapter to supplement the current textbook in the future.

Reviewed by Finn Bell, Assistant Professor, University of Michigan, Dearborn on 1/3/24

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary. read more

For it being a quick guide and only 26 pages, it is very comprehensive, but it does not include an index or glossary.

Content Accuracy rating: 5

As far as I can tell, the text is accurate, error-free and unbiased.

Relevance/Longevity rating: 5

This text is up-to-date, and given the content, unlikely to become obsolete any time soon.

Clarity rating: 5

The text is very clear and accessible.

Consistency rating: 5

The text is internally consistent.

Modularity rating: 5

Given how short the text is, it seems unnecessary to divide it into smaller readings, nonetheless, it is clearly labelled such that an instructor could do so.

Organization/Structure/Flow rating: 5

The text is well-organized and brings readers through basic quantitative methods in a logical, clear fashion.

Easy to navigate. Only one table that is split between pages, but not in a way that is confusing.

Grammatical Errors rating: 5

There were no noticeable grammatical errors.

The examples in this book don't give enough information to rate this effectively.

This text is truly a very quick guide at only 26 double-spaced pages. Nonetheless, Davies packs a lot of information on the basics of quantitative research methods into this text, in an engaging way with many examples of the concepts presented. This guide is more of a brief how-to that takes readers as far as how to select statistical tests. While it would be impossible to fully learn quantitative research from such a short text, of course, this resource provides a great introduction, overview, and refresher for program evaluation courses.

Reviewed by Shari Fedorowicz, Adjunct Professor, Bridgewater State University on 12/16/22

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing... read more

Comprehensiveness rating: 5 see less

The text is indeed a quick guide for utilizing quantitative research. Appropriate and effective examples and diagrams were used throughout the text. The author clearly differentiates between use of quantitative and qualitative research providing the reader with the ability to distinguish two terms that frequently get confused. In addition, links and outside resources are provided to deepen the understanding as an option for the reader. The use of these links, coupled with diagrams and examples make this text comprehensive.

The content is mostly accurate. Given that it is a quick guide, the author chose a good selection of which types of research designs to include. However, some are not provided. For example, correlational or cross-correlational research is omitted and is not discussed in Section 3, but is used as a statistical example in the last section.

Examples utilized were appropriate and associated with terms adding value to the learning. The tables that included differentiation between types of statistical tests along with a parametric/nonparametric table were useful and relevant.

The purpose to the text and how to use this guide book is stated clearly and is established up front. The author is also very clear regarding the skill level of the user. Adding to the clarity are the tables with terms, definitions, and examples to help the reader unpack the concepts. The content related to the terms was succinct, direct, and clear. Many times examples or figures were used to supplement the narrative.

The text is consistent throughout from contents to references. Within each section of the text, the introductory paragraph under each section provides a clear understanding regarding what will be discussed in each section. The layout is consistent for each section and easy to follow.

The contents are visible and address each section of the text. A total of seven sections, including a reference section, is in the contents. Each section is outlined by what will be discussed in the contents. In addition, within each section, a heading is provided to direct the reader to the subtopic under each section.

The text is well-organized and segues appropriately. I would have liked to have seen an introductory section giving a narrative overview of what is in each section. This would provide the reader with the ability to get a preliminary glimpse into each upcoming sections and topics that are covered.

The book was easy to navigate and well-organized. Examples are presented in one color, links in another and last, figures and tables. The visuals supplemented the reading and placed appropriately. This provides an opportunity for the reader to unpack the reading by use of visuals and examples.

No significant grammatical errors.

Cultural Relevance rating: 5

The text is not offensive or culturally insensitive. Examples were inclusive of various races, ethnicities, and backgrounds.

This quick guide is a beneficial text to assist in unpacking the learning related to quantitative statistics. I would use this book to complement my instruction and lessons, or use this book as a main text with supplemental statistical problems and formulas. References to statistical programs were appropriate and were useful. The text did exactly what was stated up front in that it is a direct guide to quantitative statistics. It is well-written and to the point with content areas easy to locate by topic.

Reviewed by Sarah Capello, Assistant Professor, Radford University on 1/18/22

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text. read more

Comprehensiveness rating: 4 see less

The text claims to provide "quick and simple advice on quantitative aspects of research in social sciences," which it does. There is no index or glossary, although vocabulary words are bolded and defined throughout the text.

The content is mostly accurate. I would have preferred a few nuances to be hashed out a bit further to avoid potential reader confusion or misunderstanding of the concepts presented.

The content is current; however, some of the references cited in the text are outdated. Newer editions of those texts exist.

The text is very accessible and readable for a variety of audiences. Key terms are well-defined.

There are no content discrepancies within the text. The author even uses similarly shaped graphics for recurring purposes throughout the text (e.g., arrow call outs for further reading, rectangle call outs for examples).

The content is chunked nicely by topics and sections. If it were used for a course, it would be easy to assign different sections of the text for homework, etc. without confusing the reader if the instructor chose to present the content in a different order.

The author follows the structure of the research process. The organization of the text is easy to follow and comprehend.

All of the supplementary images (e.g., tables and figures) were beneficial to the reader and enhanced the text.

There are no significant grammatical errors.

I did not find any culturally offensive or insensitive references in the text.

This text does the difficult job of introducing the complicated concepts and processes of quantitative research in a quick and easy reference guide fairly well. I would not depend solely on this text to teach students about quantitative research, but it could be a good jumping off point for those who have no prior knowledge on this subject or those who need a gentle introduction before diving in to more advanced and complex readings of quantitative research methods.

Reviewed by J. Marlie Henry, Adjunct Faculty, University of Saint Francis on 12/9/21

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of... read more

Considering the length of this guide, this does a good job of addressing major areas that typically need to be addressed. There is a contents section. The guide does seem to be organized accordingly with appropriate alignment and logical flow of thought. There is no glossary but, for a guide of this length, a glossary does not seem like it would enhance the guide significantly.

The content is relatively accurate. Expanding the content a bit more or explaining that the methods and designs presented are not entirely inclusive would help. As there are different schools of thought regarding what should/should not be included in terms of these designs and methods, simply bringing attention to that and explaining a bit more would help.

Relevance/Longevity rating: 3

This content needs to be updated. Most of the sources cited are seven or more years old. Even more, it would be helpful to see more currently relevant examples. Some of the source authors such as Andy Field provide very interesting and dynamic instruction in general, but they have much more current information available.

The language used is clear and appropriate. Unnecessary jargon is not used. The intent is clear- to communicate simply in a straightforward manner.

The guide seems to be internally consistent in terms of terminology and framework. There do not seem to be issues in this area. Terminology is internally consistent.

For a guide of this length, the author structured this logically into sections. This guide could be adopted in whole or by section with limited modifications. Courses with fewer than seven modules could also logically group some of the sections.

This guide does present with logical organization. The topics presented are conceptually sequenced in a manner that helps learners build logically on prior conceptualization. This also provides a simple conceptual framework for instructors to guide learners through the process.

Interface rating: 4

The visuals themselves are simple, but they are clear and understandable without distracting the learner. The purpose is clear- that of learning rather than visuals for the sake of visuals. Likewise, navigation is clear and without issues beyond a broken link (the last source noted in the references).

This guide seems to be free of grammatical errors.

It would be interesting to see more cultural integration in a guide of this nature, but the guide is not culturally insensitive or offensive in any way. The language used seems to be consistent with APA's guidelines for unbiased language.

Reviewed by Heng Yu-Ku, Professor, University of Northern Colorado on 5/13/21

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive... read more

The text covers all areas and ideas appropriately and provides practical tables, charts, and examples throughout the text. I would suggest the author also provides a complete research proposal at the end of Section 3 (page 10) and a comprehensive research study as an Appendix after section 7 (page 26) to help readers comprehend information better.

For the most part, the content is accurate and unbiased. However, the author only includes four types of research designs used on the social sciences that contain quantitative elements: 1. Mixed method, 2) Case study, 3) Quasi-experiment, and 3) Action research. I wonder why the correlational research is not included as another type of quantitative research design as it has been introduced and emphasized in section 6 by the author.

I believe the content is up-to-date and that necessary updates will be relatively easy and straightforward to implement.

The text is easy to read and provides adequate context for any technical terminology used. However, the author could provide more detailed information about estimating the minimum sample size but not just refer the readers to use the online sample calculators at a different website.

The text is internally consistent in terms of terminology and framework. The author provides the right amount of information with additional information or resources for the readers.

The text includes seven sections. Therefore, it is easier for the instructor to allocate or divide the content into different weeks of instruction within the course.

Yes, the topics in the text are presented in a logical and clear fashion. The author provides clear and precise terminologies, summarizes important content in Table or Figure forms, and offers examples in each section for readers to check their understanding.

The interface of the book is consistent and clear, and all the images and charts provided in the book are appropriate. However, I did encounter some navigation problems as a couple of links are not working or requires permission to access those (pages 10 and 27).

No grammatical errors were found.

No culturally incentive or offensive in its language and the examples provided were found.

As the book title stated, this book provides “A Quick Guide to Quantitative Research in Social Science. It offers easy-to-read information and introduces the readers to the research process, such as research questions, research paradigms, research process, research designs, research methods, data collection, data analysis, and data discussion. However, some links are not working or need permissions to access them (pages 10 and 27).

Reviewed by Hsiao-Chin Kuo, Assistant Professor, Northeastern Illinois University on 4/26/21, updated 4/28/21

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and... read more

As a quick guide, it covers basic concepts related to quantitative research. It starts with WHY quantitative research with regard to asking research questions and considering research paradigms, then provides an overview of research design and process, discusses methods, data collection and analysis, and ends with writing a research report. It also identifies its target readers/users as those begins to explore quantitative research. It would be helpful to include more examples for readers/users who are new to quantitative research.

Its content is mostly accurate and no bias given its nature as a quick guide. Yet, it is also quite simplified, such as its explanations of mixed methods, case study, quasi-experimental research, and action research. It provides resources for extended reading, yet more recent works will be helpful.

The book is relevant given its nature as a quick guide. It would be helpful to provide more recent works in its resources for extended reading, such as the section for Survey Research (p. 12). It would also be helpful to include more information to introduce common tools and software for statistical analysis.

The book is written with clear and understandable language. Important terms and concepts are presented with plain explanations and examples. Figures and tables are also presented to support its clarity. For example, Table 4 (p. 20) gives an easy-to-follow overview of different statistical tests.

The framework is very consistent with key points, further explanations, examples, and resources for extended reading. The sample studies are presented following the layout of the content, such as research questions, design and methods, and analysis. These examples help reinforce readers' understanding of these common research elements.

The book is divided into seven chapters. Each chapter clearly discusses an aspect of quantitative research. It can be easily divided into modules for a class or for a theme in a research method class. Chapters are short and provides additional resources for extended reading.

The topics in the chapters are presented in a logical and clear structure. It is easy to follow to a degree. Though, it would be also helpful to include the chapter number and title in the header next to its page number.

The text is easy to navigate. Most of the figures and tables are displayed clearly. Yet, there are several sections with empty space that is a bit confusing in the beginning. Again, it can be helpful to include the chapter number/title next to its page number.

Grammatical Errors rating: 4

No major grammatical errors were found.

There are no cultural insensitivities noted.

Given the nature and purpose of this book, as a quick guide, it provides readers a quick reference for important concepts and terms related to quantitative research. Because this book is quite short (27 pages), it can be used as an overview/preview about quantitative research. Teacher's facilitation/input and extended readings will be needed for a deeper learning and discussion about aspects of quantitative research.

Reviewed by Yang Cheng, Assistant Professor, North Carolina State University on 1/6/21

It covers the most important topics such as research progress, resources, measurement, and analysis of the data. read more

It covers the most important topics such as research progress, resources, measurement, and analysis of the data.

The book accurately describes the types of research methods such as mixed-method, quasi-experiment, and case study. It talks about the research proposal and key differences between statistical analyses as well.

The book pinpointed the significance of running a quantitative research method and its relevance to the field of social science.

The book clearly tells us the differences between types of quantitative methods and the steps of running quantitative research for students.

The book is consistent in terms of terminologies such as research methods or types of statistical analysis.

It addresses the headlines and subheadlines very well and each subheading should be necessary for readers.

The book was organized very well to illustrate the topic of quantitative methods in the field of social science.

The pictures within the book could be further developed to describe the key concepts vividly.

The textbook contains no grammatical errors.

It is not culturally offensive in any way.

Overall, this is a simple and quick guide for this important topic. It should be valuable for undergraduate students who would like to learn more about research methods.

Reviewed by Pierre Lu, Associate Professor, University of Texas Rio Grande Valley on 11/20/20

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas. read more

As a quick guide to quantitative research in social sciences, the text covers most ideas and areas.

Mostly accurate content.

As a quick guide, content is highly relevant.

Succinct and clear.

Internally, the text is consistent in terms of terminology used.

The text is easily and readily divisible into smaller sections that can be used as assignments.

I like that there are examples throughout the book.

Easy to read. No interface/ navigation problems.

No grammatical errors detected.

I am not aware of the culturally insensitive description. After all, this is a methodology book.

I think the book has potential to be adopted as a foundation for quantitative research courses, or as a review in the first weeks in advanced quantitative course.

Reviewed by Sarah Fischer, Assistant Professor, Marymount University on 7/31/20

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable). read more

It is meant to be an overview, but it incredibly condensed and spends almost no time on key elements of statistics (such as what makes research generalizable, or what leads to research NOT being generalizable).

Content Accuracy rating: 1

Contains VERY significant errors, such as saying that one can "accept" a hypothesis. (One of the key aspect of hypothesis testing is that one either rejects or fails to reject a hypothesis, but NEVER accepts a hypothesis.)

Very relevant to those experiencing the research process for the first time. However, it is written by someone working in the natural sciences but is a text for social sciences. This does not explain the errors, but does explain why sometimes the author assumes things about the readers ("hail from more subjectivist territory") that are likely not true.

Clarity rating: 3

Some statistical terminology not explained clearly (or accurately), although the author has made attempts to do both.

Very consistently laid out.

Chapters are very short yet also point readers to outside texts for additional information. Easy to follow.

Generally logically organized.

Easy to navigate, images clear. The additional sources included need to linked to.

Minor grammatical and usage errors throughout the text.

Makes efforts to be inclusive.

The idea of this book is strong--short guides like this are needed. However, this book would likely be strengthened by a revision to reduce inaccuracies and improve the definitions and technical explanations of statistical concepts. Since the book is specifically aimed at the social sciences, it would also improve the text to have more examples that are based in the social sciences (rather than the health sciences or the arts).

Reviewed by Michelle Page, Assistant Professor, Worcester State University on 5/30/20

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new... read more

This text is exactly intended to be what it says: A quick guide. A basic outline of quantitative research processes, akin to cliff notes. The content provides only the essentials of a research process and contains key terms. A student or new researcher would not be able to use this as a stand alone guide for quantitative pursuits without having a supplemental text that explains the steps in the process more comprehensively. The introduction does provide this caveat.

Content Accuracy rating: 3

There are no biases or errors that could be distinguished; however, it’s simplicity in content, although accurate for an outline of process, may lack a conveyance of the deeper meanings behind the specific processes explained about qualitative research.

The content is outlined in traditional format to highlight quantitative considerations for formatting research foundational pieces. The resources/references used to point the reader to literature sources can be easily updated with future editions.

The jargon in the text is simple to follow and provides adequate context for its purpose. It is simplified for its intention as a guide which is appropriate.

Each section of the text follows a consistent flow. Explanation of the research content or concept is defined and then a connection to literature is provided to expand the readers understanding of the section’s content. Terminology is consistent with the qualitative process.

As an “outline” and guide, this text can be used to quickly identify the critical parts of the quantitative process. Although each section does not provide deeper content for meaningful use as a stand alone text, it’s utility would be excellent as a reference for a course and can be used as an content guide for specific research courses.

The text’s outline and content are aligned and are in a logical flow in terms of the research considerations for quantitative research.

The only issue that the format was not able to provide was linkable articles. These would have to be cut and pasted into a browser. Functional clickable links in a text are very successful at leading the reader to the supplemental material.

No grammatical errors were noted.

This is a very good outline “guide” to help a new or student researcher to demystify the quantitative process. A successful outline of any process helps to guide work in a logical and systematic way. I think this simple guide is a great adjunct to more substantial research context.

Table of Contents

• Section 1: What will this resource do for you?
• Section 2: Why are you thinking about numbers? A discussion of the research question and paradigms.
• Section 3: An overview of the Research Process and Research Designs
• Section 4: Quantitative Research Methods
• Section 5: the data obtained from quantitative research
• Section 6: Analysis of data
• Section 7: Discussing your Results

Ancillary Material

About the book.

This resource is intended as an easy-to-use guide for anyone who needs some quick and simple advice on quantitative aspects of research in social sciences, covering subjects such as education, sociology, business, nursing. If you area qualitative researcher who needs to venture into the world of numbers, or a student instructed to undertake a quantitative research project despite a hatred for maths, then this booklet should be a real help.

The booklet was amended in 2022 to take into account previous review comments.  

About the Contributors

Christine Davies , Ph.D

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Quantitative Methods in the Humanities: An Introduction

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A. E. C. M.; Quantitative Methods in the Humanities: An Introduction. The Journal of Interdisciplinary History 2020; 51 (1): 137–139. doi: https://doi.org/10.1162/jinh_r_01527

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History is notoriously a “big tent” discipline. Because everything has a past, every subject has a history. The tools appropriate to ferret out those histories multiply just as easily as the topics, depending on the questions being asked and the nature of the evidence preserved (accidentally or otherwise) that might answer them. In what sense is History a coherent “discipline” at all? Is there more to hold it together than just a ferocious commitment to the past tense? Must historians adhere to a recognized and common methodology of practice, but of what might it consist, in the face of so much variety? These questions bedevil historians everywhere, especially when they are trying to figure out what their students should know and/or know how to do. Whatever the answers might be, these questions frame both the motivation for the book under review and its value for readers.

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Quantitative Research: A Successful Investigation in Natural and Social Sciences

Mohajan, Haradhan (2020): Quantitative Research: A Successful Investigation in Natural and Social Sciences. Published in: Journal of Economic Development, Environment and People , Vol. 9, No. 4 (31 December 2020): pp. 52-79.

Research is the framework used for the planning, implementation, and analysis of a study. The proper choice of a suitable research methodology can provide an effective and successful original research. A researcher can reach his/her expected goal by following any kind of research methodology. Quantitative research methodology is preferred by many researchers. This article presents and analyzes the design of quantitative research. It also discusses the proper use and the components of quantitative research methodology. It is used to quantify attitudes, opinions, behaviors, and other defined variables and generalize results from a larger sample population by the way of generating numerical data. The purpose of this study is to provide some important fundamental concepts of quantitative research to the common readers for the development of their future projects, articles and/or theses. An attempt has been taken here to study the aspects of the quantitative research methodology in some detail.

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Home » Humanities Research – Types, Methods and Examples

Humanities Research – Types, Methods and Examples

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Humanities Research

Definition:

Humanities research is a systematic and critical investigation of human culture, values, beliefs, and practices, including the study of literature, philosophy, history, art, languages, religion, and other aspects of human experience.

Types of Humanities Research

Types of Humanities Research are as follows:

Historical Research

This type of research involves studying the past to understand how societies and cultures have evolved over time. Historical research may involve examining primary sources such as documents, artifacts, and other cultural products, as well as secondary sources such as scholarly articles and books.

Cultural Studies

This type of research involves examining the cultural expressions and practices of a particular society or community. Cultural studies may involve analyzing literature, art, music, film, and other forms of cultural production to understand their social and cultural significance.

Linguistics Research

This type of research involves studying language and its role in shaping cultural and social practices. Linguistics research may involve analyzing the structure and use of language, as well as its historical development and cultural variations.

Anthropological Research

This type of research involves studying human cultures and societies from a comparative and cross-cultural perspective. Anthropological research may involve ethnographic fieldwork, participant observation, interviews, and other qualitative research methods.

Philosophy Research

This type of research involves examining fundamental questions about the nature of reality, knowledge, morality, and other philosophical concepts. Philosophy research may involve analyzing philosophical texts, conducting thought experiments, and engaging in philosophical discourse.

Art History Research

This type of research involves studying the history and significance of art and visual culture. Art history research may involve analyzing the formal and aesthetic qualities of art, as well as its historical context and cultural significance.

Literary Studies Research

This type of research involves analyzing literature and other forms of written expression. Literary studies research may involve examining the formal and structural qualities of literature, as well as its historical and cultural context.

Digital Humanities Research

This type of research involves using digital technologies to study and analyze cultural artifacts and practices. Digital humanities research may involve analyzing large datasets, creating digital archives, and using computational methods to study cultural phenomena.

Data Collection Methods

Data Collection Methods in Humanities Research are as follows:

• Interviews : This method involves conducting face-to-face, phone or virtual interviews with individuals who are knowledgeable about the research topic. Interviews may be structured, semi-structured, or unstructured, depending on the research questions and objectives. Interviews are often used in qualitative research to gain in-depth insights and perspectives.
• Surveys : This method involves distributing questionnaires or surveys to a sample of individuals or groups. Surveys may be conducted in person, through the mail, or online. Surveys are often used in quantitative research to collect data on attitudes, behaviors, and other characteristics of a population.
• Observations : This method involves observing and recording behavior or events in a natural or controlled setting. Observations may be structured or unstructured, and may involve the use of audio or video recording equipment. Observations are often used in qualitative research to collect data on social practices and behaviors.
• Archival Research: This method involves collecting data from historical documents, artifacts, and other cultural products. Archival research may involve accessing physical archives or online databases. Archival research is often used in historical and cultural studies to study the past.
• Case Studies : This method involves examining a single case or a small number of cases in depth. Case studies may involve collecting data through interviews, observations, and archival research. Case studies are often used in cultural studies, anthropology, and sociology to understand specific social or cultural phenomena.
• Focus Groups : This method involves bringing together a small group of individuals to discuss a particular topic or issue. Focus groups may be conducted in person or online, and are often used in qualitative research to gain insights into social and cultural practices and attitudes.
• Participatory Action Research : This method involves engaging with individuals or communities in the research process, with the goal of promoting social change or addressing a specific social problem. Participatory action research may involve conducting focus groups, interviews, or surveys, as well as involving participants in data analysis and interpretation.

Data Analysis Methods

Some common data analysis methods used in humanities research:

• Content Analysis : This method involves analyzing the content of texts or cultural artifacts to identify patterns, themes, and meanings. Content analysis is often used in literary studies, media studies, and cultural studies to analyze the meanings and representations conveyed in cultural products.
• Discourse Analysis: This method involves analyzing the use of language and discourse to understand social and cultural practices and identities. Discourse analysis may involve analyzing the structure, meaning, and power dynamics of language and discourse in different social contexts.
• Narrative Analysis: This method involves analyzing the structure, content, and meaning of narratives in different cultural contexts. Narrative analysis may involve analyzing the themes, symbols, and narrative devices used in literary texts or other cultural products.
• Ethnographic Analysis : This method involves analyzing ethnographic data collected through participant observation, interviews, and other qualitative methods. Ethnographic analysis may involve identifying patterns and themes in the data, as well as interpreting the meaning and significance of social and cultural practices.
• Statistical Analysis: This method involves using statistical methods to analyze quantitative data collected through surveys or other quantitative methods. Statistical analysis may involve using descriptive statistics to describe the characteristics of the data, or inferential statistics to test hypotheses and make inferences about a population.
• Network Analysis: This method involves analyzing the structure and dynamics of social networks to understand social and cultural practices and relationships. Network analysis may involve analyzing patterns of social interaction, communication, and influence.
• Visual Analysis : This method involves analyzing visual data, such as images, photographs, and art, to understand their cultural and social significance. Visual analysis may involve analyzing the formal and aesthetic qualities of visual products, as well as their historical and cultural context.

Examples of Humanities Research

Some Examples of Humanities Research are as follows:

• Literary research on diversity and representation: Scholars of literature are exploring the representation of different groups in literature and how those representations have changed over time. They are also studying how literature can promote empathy and understanding across different cultures and communities.
• Philosophical research on ethics and technology: Philosophers are examining the ethical implications of emerging technologies, such as artificial intelligence and biotechnology. They are asking questions about what it means to be human in a world where technology is becoming increasingly advanced.
• Anthropological research on cultural identity: Anthropologists are studying the ways in which culture shapes individual and collective identities. They are exploring how cultural practices and beliefs can shape social and political systems, as well as how individuals and communities resist or adapt to dominant cultural norms.
• Linguistic research on language and communication: Linguists are studying the ways in which language use and communication can impact social and political power dynamics. They are exploring how language can reinforce or challenge social hierarchies and how language use can reflect cultural values and norms.

How to Conduct Humanities Research

Conducting humanities research involves a number of steps, including:

• Define your research question or topic : Identify a question or topic that you want to explore in-depth. This can be a broad or narrow topic, depending on the scope of your research project.
• Conduct a literature review: Before beginning your research, read extensively on your topic. This will help you understand the existing scholarship and identify gaps in the literature that your research can address.
• Develop a research methodology: Determine the methods you will use to collect and analyze data, such as interviews, surveys, archival research, or textual analysis. Your methodology should be appropriate to your research question and topic.
• Collect data: Collect data using the methods you have chosen. This may involve conducting interviews, surveys, or archival research, or analyzing primary or secondary sources.
• Analyze data: Once you have collected data, analyze it using appropriate methods. This may involve coding, categorizing, or comparing data, or interpreting texts or other sources.
• Draw conclusions: Based on your analysis, draw conclusions about your research question or topic. These conclusions should be supported by your data and should contribute to existing scholarship.
• Communicate your findings : Communicate your findings through writing, presentations, or other forms of dissemination. Your work should be clearly written and accessible to a broad audience.

Applications of Humanities Research

Humanities research has many practical applications in various fields, including:

• Policy-making: Humanities research can inform policy-making by providing insights into social, cultural, and historical contexts. It can help policymakers understand the impact of policies on communities and identify potential unintended consequences.
• Education: Humanities research can inform curriculum development and pedagogy. It can provide insights into how to teach critical thinking, cross-cultural understanding, and communication skills.
• Cultural heritage preservation: Humanities research can help to preserve cultural heritage by documenting and analyzing cultural practices, traditions, and artifacts. It can also help to promote cultural tourism and support local economies.
• Business and industry: Humanities research can provide insights into consumer behavior, cultural preferences, and historical trends that can inform marketing, branding, and product design.
• Healthcare : Humanities research can contribute to the development of patient-centered healthcare by exploring the impact of social and cultural factors on health and illness. It can also help to promote cross-cultural understanding and empathy in healthcare settings.
• Social justice: Humanities research can contribute to social justice by providing insights into the experiences of marginalized communities, documenting historical injustices, and promoting cross-cultural understanding.

Purpose of Humanities Research

The purpose of humanities research is to deepen our understanding of human experience, culture, and history. Humanities research aims to explore the human condition and to provide insights into the diversity of human perspectives, values, and beliefs.

Humanities research can contribute to knowledge in various fields, including history, literature, philosophy, anthropology, and more. It can help us to understand how societies and cultures have evolved over time, how they have been shaped by various factors, and how they continue to change.

Humanities research also aims to promote critical thinking and creativity. It encourages us to question assumptions, to challenge dominant narratives, and to seek out new perspectives. Humanities research can help us to develop empathy and understanding for different cultures and communities, and to appreciate the richness and complexity of human experience.

Overall, the purpose of humanities research is to contribute to a deeper understanding of ourselves, our communities, and our world. It helps us to grapple with fundamental questions about the human experience and to develop the skills and insights needed to address the challenges of the future.

When to use Humanities Research

Humanities research can be used in various contexts where a deeper understanding of human experience, culture, and history is required. Here are some examples of when humanities research may be appropriate:

• Exploring social and cultural phenomena: Humanities research can be used to explore social and cultural phenomena such as art, literature, religion, and politics. It can help to understand how these phenomena have evolved over time and how they relate to broader social, cultural, and historical contexts.
• Understanding historical events: Humanities research can be used to understand historical events such as wars, revolutions, and social movements. It can provide insights into the motivations, experiences, and perspectives of the people involved, and help to contextualize these events within broader historical trends.
• Promoting cultural understanding : Humanities research can be used to promote cross-cultural understanding and to challenge stereotypes and biases. It can provide insights into the diversity of human experiences, values, and beliefs, and help to build empathy and mutual respect across different cultures and communities.
• Informing policy-making: Humanities research can be used to inform policy-making by providing insights into social, cultural, and historical contexts. It can help policymakers understand the impact of policies on communities and identify potential unintended consequences.
• Promoting innovation and creativity : Humanities research can be used to promote innovation and creativity in various fields. It can help to generate new ideas, perspectives, and approaches to complex problems, and to challenge conventional thinking and assumptions.

Characteristics of Humanities Research

Some of the key characteristics of humanities research:

• Focus on human experience: Humanities research focuses on the study of human experience, culture, and history. It aims to understand the human condition, explore human values and beliefs, and analyze the ways in which societies and cultures have evolved over time.
• Interpretive approach: Humanities research takes an interpretive approach to data analysis. It seeks to understand the meaning behind texts, artifacts, and cultural practices, and to explore the multiple perspectives and contexts that shape human experience.
• Contextualization : Humanities research emphasizes the importance of contextualization. It seeks to understand how social, cultural, and historical factors shape human experience, and to place individual phenomena within broader cultural and historical contexts.
• Subjectivity : Humanities research recognizes the subjective nature of human experience. It acknowledges that human values, beliefs, and experiences are shaped by individual perspectives, and that these perspectives can vary across cultures, communities, and time periods.
• Narrative analysis : Humanities research often uses narrative analysis to explore the stories, myths, and cultural narratives that shape human experience. It seeks to understand how these narratives are constructed, how they evolve over time, and how they influence individual and collective identity.
• Multi-disciplinary: Humanities research is often interdisciplinary, drawing on a range of disciplines such as history, literature, philosophy, anthropology, and more. It seeks to bring together different perspectives and approaches to understand complex human phenomena.

Advantages of Humanities Research

Some of the key advantages of humanities research:

• Promotes critical thinking: Humanities research encourages critical thinking by challenging assumptions and exploring different perspectives. It requires researchers to analyze and interpret complex texts, artifacts, and cultural practices, and to make connections between different phenomena.
• Enhances cultural understanding : Humanities research promotes cross-cultural understanding by exploring the diversity of human experiences, values, and beliefs. It helps to challenge stereotypes and biases and to build empathy and mutual respect across different cultures and communities.
• Builds historical awareness: Humanities research helps us to understand the historical context of current events and social issues. It provides insights into how societies and cultures have evolved over time and how they have been shaped by various factors, and helps us to contextualize current social, political, and cultural trends.
• Contributes to public discourse: Humanities research contributes to public discourse by providing insights into complex social, cultural, and historical phenomena. It helps to inform public policy and public debate by providing evidence-based analysis and insights into social issues and problems.
• Promotes creativity and innovation: Humanities research promotes creativity and innovation by challenging conventional thinking and assumptions. It encourages researchers to generate new ideas and perspectives and to explore alternative ways of understanding and addressing complex problems.
• Builds communication skills: Humanities research requires strong communication skills, including the ability to analyze and interpret complex texts, artifacts, and cultural practices, and to communicate findings and insights in a clear and compelling way.

Limitations of Humanities Research

Some of the key limitations of humanities research:

• Subjectivity: Humanities research relies heavily on interpretation and analysis, which are inherently subjective. Researchers bring their own perspectives, biases, and values to the analysis, which can affect the conclusions they draw.
• Lack of generalizability : Humanities research often focuses on specific texts, artifacts, or cultural practices, which can limit the generalizability of findings to other contexts. It is difficult to make broad generalizations based on limited samples, which can be a challenge when trying to draw broader conclusions.
• Limited quantitative data : Humanities research often relies on qualitative data, such as texts, images, and cultural practices, which can be difficult to quantify. This can make it difficult to conduct statistical analyses or to draw quantitative conclusions.
• Limited replicability: Humanities research often involves in-depth analysis of specific texts, artifacts, or cultural practices, which can make it difficult to replicate studies. This can make it challenging to test the validity of findings or to compare results across studies.
• Limited funding: Humanities research may not always receive the same level of funding as other types of research. This can make it challenging for researchers to conduct large-scale studies or to have access to the same resources as other researchers in different fields.
• Limited impact : Humanities research may not always have the same level of impact as research in other fields, particularly in terms of policy and practical applications. This can make it challenging for researchers to demonstrate the relevance and impact of their work.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Doing Quantitative Research in the Humanities

by aseifert | Apr 17, 2015 | History & Classics , Languages & Literature , Philosophy , Politics & Law , Training and Research | 0 comments

Data can be described as quantitative if it can be measured or identified on a numerical scale. Examples include length, height, area, volume, weight, speed, age, distance, cost and so on. However, not all data using numbers is quantitative: Datasets are often classified into categorical data, i.e. using numbers as descriptors. Arithmetic performed on the numbers describing categorical data would produce nonsensical results, for the same reason that you cannot add 6 Acacia Road to 12 Acacia Road to create 18 Acacia Road. Be wary, therefore, when you consider a dataset.

What exactly do the numbers represent? If your numbers answer a question beginning ‘how many’ or ‘how much’, you have quantitative data. If your numbers represent groups or classes, you have qualitative data expressed categorically. The appropriate analytical techniques will vary accordingly.

This new tutorial on PORT and developed by the School of Advanced Study, is designed to give you the ability to approach quantitative work with confidence, even if you have no prior statistical experience. It will provide a grounding in the collection and analysis of numerical data and give you the tools to report your own results and think critically about those of others.

The Quantitative Methods tutorial can be found on the School of Advanced Study PORT website alongside other online research training resources for humanities postgraduate and early career researchers.

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Quantitative Methods for the Social Sciences

A Practical Introduction with Examples in SPSS and Stata

• Daniel Stockemer   ORCID: https://orcid.org/0000-0003-3502-6828 0

School of Political Studies, University of Ottawa, Ottawa, Canada

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• Offers an essential introduction to survey research and quantitative methods
• Teaches statistical methods in a practical, hands-on manner
• Shows how to conduct empirical tests in SPSS and Stata

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Table of contents (9 chapters)

Front matter, introduction.

Daniel Stockemer

The Nuts and Bolts of Empirical Social Science

A short introduction to survey research, constructing a survey, conducting a survey, univariate statistics, bivariate statistics with categorical variables, bivariate relationships featuring two continuous variables, multivariate regression analysis, back matter.

• Quantitative Methods in Social Sciences
• Statistics in Social Sciences
• Practical Approach to Survey Research
• Introductory Statistics

Book Title : Quantitative Methods for the Social Sciences

Book Subtitle : A Practical Introduction with Examples in SPSS and Stata

Authors : Daniel Stockemer

DOI : https://doi.org/10.1007/978-3-319-99118-4

Publisher : Springer Cham

eBook Packages : Social Sciences , Social Sciences (R0)

Copyright Information : Springer International Publishing AG 2019

eBook ISBN : 978-3-319-99118-4 Published: 19 November 2018

Edition Number : 1

Number of Pages : IX, 181

Number of Illustrations : 27 b/w illustrations, 93 illustrations in colour

Topics : Methodology of the Social Sciences , Statistics for Social Sciences, Humanities, Law , Statistics and Computing/Statistics Programs

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