Beginning Quantitative Research

Malcolm Williams,Richard Wiggins,Paul R. Vogt

• Editore: SAGE Publications Ltd
• Anno: 2022
• ISBN:
  9781529710755
• Edizione: 1
• Argomento: Social Sciences
• Categoria: Social Science Research & Methodology

This concise text provides a clear and digestible introduction to completing quantitative research. Taking you step-by-step through the process of completing your quantitative research project, it offers guidance on:

· Formulating your research question

· Completing literature reviews and meta-analysis

· Formulating a research design and specifying your target population and data source

· Choosing an appropriate method and analysing your findings

Part of The SAGE Quantitative Research Kit, this book will give you the know-how and confidence needed to succeed on your quantitative research journey.

1 A General Introduction to This Kit

Malcolm Williams

Richard D. Wiggins

W. Paul Vogt†

Chapter Overview

• What is social research? 2
• What is quantitative research? 2
• What The SAGE Quantitative Research Kit will do 3
• About this volume 4
• Further Reading 5

What is social research?

Social research is investigation in social science. Investigation allows social scientists to understand, explain and predict the social world. It is an enormously varied enterprise in both scale and methods. It encompasses everything from the micro-methods of small-group research, or research of individuals, to big data research, that gathers information from, sometimes, millions of social interactions. Unsurprisingly, the scale and variation in the nature of research leads to quite different methodological approaches. Broadly speaking, these can be divided into qualitative and quantitative methods, and whilst each of these has their origins in quite different philosophical traditions, in practice the divide is not always sharp. Indeed, many research programmes will employ both quantitative and qualitative approaches, in what is known as ‘mixed methods’ (Tashakkori & Teddle, 2010). Furthermore, some new approaches, in particular those that use data from new social media, blur the distinction between quantitative and qualitative research (Williams, 2021).

Social research matters because it is able to tell us what human societies are like. It is able to provide explanations of behaviour, beliefs and intentions at both micro and macro levels. Advanced societies cannot do without social research, and if there was ever any doubt in that, the COVID-19 pandemic, that began in early 2020, demonstrates this. Understanding the prevalence and spread of the disease, and the behaviours that accelerate or help to control these things, is as much about knowledge of the social phenomenon as it is about biology. For example, at a macro level what is the nature of population movement and behaviours that impact on prevalence and spread, and at a micro level how do we understand individual beliefs and behaviours?

This is but one example, current at the time of writing, but it takes little imagination to grasp the relevance of research to society in so many fields of, for example, criminal justice, education, housing, employment, gender and ethnicity. Many of these interact in complex ways, and so often social researchers must investigate problems that span these fields with a range of methodological tools. The tools, like the problems, range from the simple to the sophisticated, but behind these tools, there is methodological reasoning for their optimum use.

The SAGE ‘Kits’ (previously known as the SAGE Qualitative Methods Kit) and the current SAGE Quantitative Research Kit, aim to introduce social researchers to the tools and the reasoning behind their use.

What is quantitative research?

Quantitative research is about quantities. It is about measurement: how much of something there is, how long something has been happening or about explaining why something happened and possibly predicting if, or to what extent, it will happen in the future. Quantitative research is almost inevitably defined in contrast with qualitative research. And, of course, the converse is also true. Following that convention, the simplest, rule-of-thumb definition of quantitative research would be investigations in which the data that are collected and coded are expressible as numbers. By contrast, studies in which data are collected and coded as words would be instances of qualitative research. Weightier distinctions have also been important in discussions of research methods – distinctions bordering on epistemologies, worldviews and ontologies, to name a few. For our purposes, we will mostly leave those discussions to more philosophically directed books (Blaikie, 2007; Kincaid, 1996).

Quantitative research is grounded in the scientific tradition, so description and inference with the potential to lead to causal explanation and prediction are its core business. Its methods are those of the experiment, the social survey or the analysis of official statistics or naturally occurring data. It can take many forms from a local neighbourhood survey to large-scale population surveys with several thousand people taking part. It may be a carefully controlled experiment in a laboratory, or it might be ‘big-data’ analysis of millions of Twitter feeds (e.g. see Sloan, 2017). Increasingly, social researchers are conducting analyses using very large government-sponsored data sets, such as Understanding Society (www.understandingsociety.ac.uk/) or the Labour Force Survey (www.ons.gov.uk/surveys/informationforhouseholdsandindividuals/householdandindividualsurveys/labourforcesurveylfs) in the UK, and the Panel Study of Income Dynamics in the USA (https://psidonline.isr.umich.edu/). The number of participants in these studies run to many thousands, allowing quite sophisticated data analysis techniques to be used.

What The SAGE Quantitative Research Kit will do

The SAGE Quantitative Research Kit is intended to help and advise you through the design and execution of your research and, importantly, in analysing your results. Your research may consist of a relatively simple survey that you have to design from the beginning, or it may be a secondary analysis of existing data. In this Kit, you will be taken on a journey from initial methodological and design issues, through relatively basic statistical techniques, through sampling, experimental and survey design to analysis. Each volume is written by experts in the particular area of design or analysis. The volumes themselves are free-standing, but equally will help to build your knowledge base of quantitative methods from the basic, but important, techniques to quite advanced approaches to analysis.

At every stage the particular volume is a conduit to the literature in that approach and to research which has used this. Most of the volumes on analysis techniques are supported by online materials, though they are not necessarily detailed manuals on how to carry out a particular task in a menu-driven software package like IBM SPSS Statistics Software (“SPSS”) (Pallant, 2020) or guides to writing your own programs in R (Wickham & Grolemund, 2017); they will tell where you can find such instructions.

About this volume

This volume is the starting point, or the foundation for the rest, and is aimed at those beginning quantitative research, or as a refresher in quantitative research before starting on the more specific volumes. The first part of this volume introduces you to some foundational theoretical and procedural concepts. Much of this is not covered elsewhere in The SAGE Quantitative Research Kit, though in line with other volumes, we will indicate where you can read in more depth on these topics. However, some of the chapters do introduce the subject matter of other volumes and might be seen as a ‘primer’ for these. So you will encounter some topics in this volume that you will encounter in much greater detail in later volumes. If you are new to social research, or to quantitative social research, the present volume will get you to the point of readiness to begin on the topic-specific volumes which follow.

In the next chapter, we begin with the starting point for any quantitative study – that of the research question. Where do research questions come from, how do we formulate them and how do we turn them into testable propositions that might be used either in surveys or experiments you design or in using existing data to answer your research question (or questions).

Chapter 3 is concerned with literature reviews and meta-analysis. A literature review is not an aesthetic critique but rather an overview and description of what we know of the topic area, whereas a meta-analysis, or systematic review, is a way to systematically conduct quantitative reviews of previous research.

In Chapter 4, we begin by considering the issue of research resources and the limits this places on research. However, most of the chapter introduces the four basic designs of social research: (1) experimental, (2) cross-sectional, (3) longitudinal and (4) case study and how these might be combined and how they relate to methods.

Research questions are closely linked to the population to which they apply. A ‘population’ may be people, or it could be schools, countries, companies and so on. In Chapter 5, we show how populations may be defined and how they may be sampled, in order to produce statistical inferences about them.

The research question, the type of population of interest and the way we access and sample it will make difference to the methods we use. We may, for example, choose to conduct a survey, which may be, for example, online, face to face or telephone. Or, we may find that there are already secondary data available for the population, which requires us only to further analyse them. In Chapters 6 and 7, we describe some of these choices and crucially how they shape and will be shaped by our strategy for the analysis of the data.

In Chapter 8, we consider some of the background assumptions that shape our research and how we should act as ethical researchers. No research exists in a social vacuum, and the questions that interest us (or indeed that we are paid to research) are located in the social and political worlds we live in. So, given this, how can we be objective scientists who are also sensitive to the sensitivities, confidence and anonymity of our respondents?

The final chapter in this volume is the springboard into the others. In this chapter, we show how the concepts discussed in the book so far are carried forward by each of the other volumes and what you might expect in those volumes.

Chapter Summary

• This chapter introduces you to social research and why social research is relevant and important.
• The chapter describes quantitative and qualitative methods and their origins in different philosophical positions.
• The chapter is concerned with quantitative research as grounded in the scientific tradition of description, explanation and prediction.
• The chapter informs us what to expect from The SAGE Quantitative Research Kit and from this volume.

Further Reading

Blaikie, N. (2007). Approaches to social enquiry (2nd ed.). Polity.

This book is an excellent review of the ways in which social research can be carried out and the epistemologies that underpin them and sometimes create tensions between them.

Vogt, W. P. (2005). Dictionary of statistics and methodology: A non-technical guide for the social sciences (3rd ed.) Sage.

This dictionary is the ‘go-to’ place to clarify, in very basic terms, concepts and statistical language.

Williams, M. (2016). Key concepts in the philosophy of social research. Sage.

This book introduces the key philosophical issues (e.g. objectivity, probability and statistical reasoning) that underpin social research. Two other basic, but very accessible ‘go-to’ books for research terms, problems and concepts are the following:

Payne, G., & Payne, J. (2004). Key concepts in social research. Sage.

Salkind, N. (2012). 100 questions (and answers) about research methods. Sage.

2 Starting With the Basics: From Research Problem to Variables

Chapter Overview

• Research problems 8
• Research questions 9
• The role of theory in research 10
• Variables 12
• Cases 13
• Research hypotheses and measures 14
• Description and explanation, and causes 16
• Conclusion 19
• Further Reading 19

Research problems

The philosopher of science Karl Popper often said that we are students of a problem, not a discipline. All interesting and useful science begins with a problem to be solved. In social research, this is often a ‘social problem’, for example, why do young women not enter engineering professions in some countries but not others (Godfroy Genin & Pinault, 2011)? Does teenage drug taking lead to later relationship problems (Newcomb & Bentler, 1988)? How many homeless people are there in a particular city (Williams & Cheal, 2001)? Sometimes the problem may be more methodological, for example, can new social media methods better predict crime levels than traditional surveys (Williams et al., 2016), or it may ‘test’ some existing theory, such as migrants have greater resources in their originating society than non-migrants (Musgrove, 1963). An interesting characteristic of social research is what is a problem in one time or place may not be a problem in another time or place. So often research is comparative to test whether a ‘problem’ is location or time-specific. For example, see Zmerli and Hooghe (2011).

Not all problems can be successfully tackled through social research, either because (as in all science) we simply don’t have the methodological capability or they are not problems that can be resolved with the resources available. Research questions often arise out of perceived social issues or ...

Indice dei contenuti

• Cover
• Half Title
• Acknowledgements
• Title Page
• Copyright Page
• Acknowledgements
• Contents
• Illustration List
• About the Authors
• 1 A General Introduction to This Kit
• 2 Starting With the Basics: From Research Problem to Variables
• 3 Literature Reviews and Meta-Analyses
• 4 Research Design and Research Resources
• 5 Sampling
• 6 Creating Data: An Introduction to Surveys and Questionnaires
• 7 Secondary Analysis and Data Manipulation
• 8 The Social Context of Quantitative Research
• 9 Conclusion and Future Directions
• Glossary
• References
• Index