Psychology
Quantitative and Qualitative Data
Quantitative data in psychology refers to numerical information that can be measured and analyzed using statistical methods, such as test scores or reaction times. Qualitative data, on the other hand, involves non-numeric information that is descriptive and subjective, such as observations or interviews. Both types of data are valuable in psychological research, providing different insights and perspectives.
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11 Key excerpts on "Quantitative and Qualitative Data"
- Aparna Raghvan(Author)
- 2020(Publication Date)
- Society Publishing(Publisher)
Each primary type of qualitative data plays an important role in highlighting unique and valuable perspectives about student learning to the outcomes-based assessment process. When it is used in combination with each other, a more holistic or complete picture of student learning is created. 7.4. WHAT’S THE DIFFERENCE BETWEEN QUALI-TATIVE AND QUANTITATIVE RESEARCH? There exists a fundamental distinction between two types of data: Quantitative data is information about quantities, and therefore includes numbers, while on the other hand, qualitative data regards phenomena which can be observed but cannot be measured in terms of numerical values, such as language (Figure 7.3 and Table 7.1). Figure 7.3. Quantitative way to compare data. Source: Image by State.gov. Table 7.1. Difference between Qualitative Research and Quantitative Research Qualitative Quantitative Conceptual It is basically concerned with under-standing behavior of people from the perspective of respondent. Assumes a dynamic and negotiated reality. It is generally interested in discovering facts about social phenom-ena. Assumes a fixed and measurable reality. Research and Evaluation in Education and Psychology 170 Methodological Data are collected through various means such as interviews and partici-pant observation method. Data are analyzed by informant with the help of themes from descriptions. Data are recorded and stored in the native language of informant. Data are collected through measuring things and gaining an insight into certain key facts. Data are analyzed through statistical infer-ences and numerical comparisons. Data are reported through statistical analyses. 7.4.1. Qualitative Research There has been a significant increase in the interest of using qualitative data because of the dissatisfaction of some psychologists (e.g., Carl Rogers) with the scientific study of psychologists such as the behaviorists (e.g., Skinner).
- Lorelle J. Burton, Drew Westen, Robin M. Kowalski(Authors)
- 2022(Publication Date)
- Wiley(Publisher)
Taking a qualitative research approach enables researchers to study phenom- ena in their natural settings and uncover a deeper meaning of phenomena. Pdf_Folio:226 226 Psychology SUMMARY 5.1 Describe the characteristics of quantitative research methods in psychology. • Psychologists might engage in quantitative research (e.g., exper- iments or surveys that provide data that can be quantified) or qual- itative research (e.g., interviews, observation and case studies to gain a richer understanding of the relevant phenomena), depending on the nature of their research question. • Empirical or scientific psychological research is characterised by a theoretical framework, standardised procedures, generalisability and objective measurement. • A theory is a systematic way of organising and explaining obser- vations that includes a set of propositions about the relationships among various phenomena. A hypothesis is a tentative belief or educated guess that purports to predict or explain the relationship between two or more variables; variables are phenomena that differ or change across circumstances or individuals. A variable that can be placed on a continuum is a continuous variable. A variable comprised of groupings or categories is a categorical variable. • A sample is a subgroup of a population that is likely to be representative of the population as a whole. Generalisability refers to the applicability of findings based on a sample to the entire population of interest. For a study’s findings to be generalisable, its methods must be sound, or valid. • A measure is a concrete way of assessing a variable. A good measure is both reliable and valid. Reliability refers to a measure’s ability to produce consistent results. The validity of a measure refers to its ability to assess the construct it is intended to measure. • The scientific approach uses empirical methodologies such as observation and experimentation to gain knowledge.
eBook - PDF- Aparna Raghvan(Author)
- 2023(Publication Date)
- Society Publishing(Publisher)
Some of the histories of qualitative psychology that have been published should be viewed with caution. It is all too often thought that approaches that are essentially devoid of statistics and numbers are qualitative in character. In these histories, for example, Freud’s work is frequently referred to as qualitative. However, this overlooks his work’s roots in positivism and its lack of a really qualitative mindset. One reason for this is that the qualitative renaissance, which began in the 1980s and accelerated in the 1990s, appears to have ushered in the development of qualitative data analysis tools previously unavailable in psychology. The histories of qualitative data collection and qualitative data analysis do not entirely coincide perfectly. The confusion is exacerbated by the use of overlapping terms. For example, while DA as a tool for qualitative psychology was developed in the 1980s, references to DA can be found far earlier – but relating to quantitative approaches. Qualitative Research in Psychology: A Brief Introduction 9 While databases can help us in tracking psychological publications all the way back to the 1800s, terminology evolves over time. As a result, earlier publications may use similar terms, but not in the present sense. The concept of qualitative research appears to be relatively new, yet no one seems to know when it first appeared—perhaps it was imported into psychology. Of course, reviewing the immense output of psychology over the last century or so in the hopes of distinguishing what is qualitative in nature would be difficult – there are currently over three million psychological research articles in print! And the number is on the rise. 1.4.2. Tracking Qualitative Methods Using PsycINFO and Other Indicators Despite this, using the huge digital datasets available to psychologists is the most effective way of documenting the emergence of qualitative psychology.
eBook - PDFPractical Research Methods in Education
An Early Researcher's Critical Guide
- Mike Lambert(Author)
- 2019(Publication Date)
- Routledge(Publisher)
This chapter rejects this view, taking as its starting point the notion that researchers should view them merely as different types of data and that they therefore need to understand how both are collected, analysed and interpreted. As using the quantitative option can seem particularly problematic, here are three reasons why readers who are nervous of numbers should con- sider familiarizing themselves with quantitative data processes: • Having some understanding of quantitative data will improve your ability to assess investigations which use quantitative approaches, particularly if you are new to research. • Being able to incorporate quantitative data into your own research could strengthen its impact, particularly if you are interested in influencing aspects of education practice or policy. Although they often use them carelessly and unreflectively, policymakers like numbers. • Having an improved understanding of quantitative data and research will put you in a better position to evaluate or conduct mixed-methods investigations. 56 Michael Jopling What is quantitative research? What are quantitative data? The application of quantitative methods in social-science research derives from interest in the 19th century in experimental investigation in the natural sciences. This sought to understand the processes of cause and effect through manipulation and controlled testing. However, it became clear that many of the issues explored in social sciences, such as educa- tion, do not lend themselves well to experimental approaches, so researchers began from the 1950s to apply them to what became known as ‘quasi-experimental’ and ‘non-experimental’ situations – these approaches are considered in more detail later in the chapter. Provocatively, Berliner (2002:19) has described what social scientists, and particularly educational researchers, do as the ‘hardest to do science […] because humans in schools are embedded in complex and changing networks of social interaction’.
eBook - PDFSuccessful Dissertations
The Complete Guide for Education, Childhood and Early Childhood Studies Students
- Caron Carter(Author)
- 2018(Publication Date)
- Bloomsbury Academic(Publisher)
The overall aim of this chapter is to convey the essence of what is involved when using quantitative methods. The chapter begins by exploring the suitability of quantitative methods to an area of study. Variables, the mainstay of quantitative research, are discussed at length, in terms of how they are defined, categorized and measured. Quantitative data can be obtained in a number of ways, such as by asking questions (using questionnaires or interview schedules), observing and recording behaviour, and through reviewing existing documents. This chapter therefore outlines some of the key features of the more common methods used by undergraduate students, with reference to some of their strengths and limitations. The what, why and when of quantitative methods What are quantitative methods? Quantitative methods are used to gather factual or attitudinal information in numerical form. Therefore, they are used to ascertain how much, how many, how frequently and/or, to what extent something occurs or exists, be this a fact or an attitude. It is worth noting that quantitative data do not necessarily start off in numerical form; they can often take the form of words which researchers later translate, by means of applying numerical codes, into numbers. Quantitative research conceptualizes reality in terms of variables and the relationships between them and relies on numbers, counts and measurements in order that these relationships can be portrayed using tables, charts and graphs. Data is generated through asking questions and getting responses (self-report methods) or by observing and recording past (secondary) or present behaviour. Why and when is it appropriate to use quantitative methods? Students are often unsure as to whether quantitative, qualitative or a combination of both methods are called for, hence the inclusion here of some information that will hopefully aid this crucial decision.
eBook - PDF- Aparna Raghvan(Author)
- 2023(Publication Date)
- Society Publishing(Publisher)
Data encoded as variables, again, do not reflect such qualitative changes of mental operations that underlie externally similar answers (see also Toomela, 2008, in press-b). Between variables postulate the interpretability of covariations. By analyzing correlations of variables, modern quantitative psychology also assumes that components of mental attributes can be discovered. This postulate is questionable as well. As a rule, from the same elements in qualitatively different relationships qualitatively different wholes emerge. However, quantitative data analysis is not suitable for taking the quality of relationships into account. For example, human language is based on units – words – that are composed in different relationships from a limited number of sounds or letters. We can take a series of events, words, and find perfect covariation between variables, sounds, in those events. Let us take, for instance, a series of events – words – this-shit-hits-pool-loop-polo. From our observation of Quantitative Research in Psychology: A Brief 27 those six cases, it creates the following data-file so that variables represent presence or absence of letters in each event/word. With those data and would not get any closer to understanding what is happening one could make many different statistical analyzes. It would discover that this data set can be perfectly “explained” by one factor, etc., perhaps one would discover that all variables are perfectly correlated. Statistically, for a quantitative scientist such results would be a perfect dream. And yet all this would have no meaning. In the table the data show where the problem is – after quantification first three and last three qualitatively different cases are identical. Here it is unknown when solving usual scientific problems, it is known that the cases are not identical.
eBook - PDFPsychology
Selected Papers
- Gina Rossi(Author)
- 2012(Publication Date)
- IntechOpen(Publisher)
Section 5 Qualitative Psychology 10 Qualitative Research Methods in Psychology Deborah Biggerstaff Warwick Medical School University of Warwick, Coventry UK 1. Introduction In the scientific community, and particularly in psychology and health, there has been an active and ongoing debate on the relative merits of adopting either quantitative or qualitative methods, especially when researching into human behaviour (Bowling, 2009; Oakley, 2000; Smith, 1995a, 1995b; Smith, 1998). In part, this debate formed a component of the development in the 1970s of our thinking about science. Andrew Pickering has described this movement as the “sociology of scientific knowledge” (SSK), where our scientific understanding, developing scientific ‘products’ and ‘know-how’, became identified as forming components in a wider engagement with society’s environmental and social context (Pickering, 1992, pp. 1). Since that time, the debate has continued so that today there is an increasing acceptance of the use of qualitative methods in the social sciences (Denzin & Lincoln, 2000; Morse, 1994; Punch, 2011; Robson, 2011) and health sciences (Bowling, 2009; Greenhalgh & Hurwitz, 1998; Murphy & Dingwall, 1998). The utility of qualitative methods has also been recognised in psychology. As Nollaig Frost (2011) observes, authors such as Carla Willig and Wendy Stainton Rogers consider qualitative psychology is much more accepted today and that it has moved from “the margins to the mainstream in psychology in the UK.” (Willig & Stainton Rogers, 2008, pp. 8). Nevertheless, in psychology, qualitative methodologies are still considered to be relatively ‘new’ (Banister, Bunn, Burman, et al., 2011; Hayes, 1998; Richardson, 1996) despite clear evidence to the contrary (see, for example, the discussion on this point by Rapport et al., 2005).
eBook - PDF- Irene Hall, Jo Campling(Authors)
- 2017(Publication Date)
- Red Globe Press(Publisher)
speed and accuracy in analysis. But while such programs offer assistance, they do not remove the need for the researcher to understand the underlying rationale of analysis in order to control the process and choose the most appropriate ways of sorting, collating and presenting their information. Interpreting the findings still relies on the researcher's skill and judgement. As with Chapter 4, there is much that has been written on the analysis of data, both from survey questionnaires and from quali-tative interviews. Within this chapter, it is only possible to present an outline of the most common approaches to quantitative and quali-tative data; a short list of suggested reading is included at the end. QUANTITATIVE OR STRUCTURED DATA Data and the rules of measurement As Chapter 4 noted, quantitative research involves turning abstract concepts into concrete indicators which can be measured through the process known as operationalization . Indicators are what can be researched and the researcher needs to identify specific factors which are variables. In planning the research, links between vari-ables were hypothesized. The analytical stage is the opportunity to test whether links exist and, if they do, how strong the connections are ± for instance between the age of respondents (variable one) and their level of satisfaction with a program (variable two). A variable has a set of categories and there are rules about how the different categories may be analysed, depending on the scale or level of measurement being used. Variables may be measured at different `levels of measurement' (depending on the type of variable), and the level of measurement will determine what kinds of analyses may be performed. (Rose and Sullivan, 1996: 17) Three different scales or levels of measurement for variables are usually distinguished as nominal; ordinal; interval/ratio. A NALYSING THE D ATA 137
- Trisha M. Greenhalgh, John Bidewell, Jane Warland, Amanda Lambros, Elaine Crisp(Authors)
- 2019(Publication Date)
- Wiley(Publisher)
Another way to illustrate the difference between qualitative and quantitative is the following example, as told by the late Dr Cecil Helman to Trisha Greenhalgh. A small child runs in from the garden and says, excitedly, ‘Mummy, the leaves are falling off the trees’. ‘Tell me more’, says his mother. That child will become a quantitative researcher because he is simply analysing numbers. A second child, when asked ‘tell me more’, might reply, ‘Well, the leaves are big and flat, and mostly yellow or red, and they seem to be falling off some trees but not others. And mummy, why did no leaves fall last month?’ That child will become a qualitative researcher because she is looking into the meaning and depth of what the leaves are. 1 ............................................................................................................................................................................ DISCUSSION QUESTIONS 1. In what situations would qualitative research be more useful than quantitative research? 2. Would research using only qualitative methods be as useful as research using a mix of qualitative and quantitative (known as ‘mixed’) methods? 3. What are the benefits of using a qualitative approach? 4.1 Qualitative research explained LEARNING OBJECTIVE 4.1 What is qualitative research? Qualitative researchers seek a deeper truth. They aim to ‘study things in their natural setting, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them’, and they use ‘a holistic perspective which preserves the complexities of human behaviour’. 2 They argue that a counting- and-measuring approach, a purely quantitative approach, limits the results of a study. Epidemiologist Nick Black has argued that a finding or result is more likely to be accepted as a fact if it is quantified (expressed in numbers) than if it is not.
eBook - PDF- Colin Robson(Author)
- 2024(Publication Date)
- Wiley(Publisher)
But, for those who do wish to work within the kind of scientific framework advocated in this book and to persuade scientific or policymaking audiences, there are ways in which qualitative data can be dealt with systematically. The present chapter seeks to provide an introduction to that task. In the typology of research strategies that has been adopted here, the various types of flexible and mixed designs are the prime generators of large amounts of complex qualitative data. Qualitative data are often useful in supplementing and illustrating the quantitative data obtained from an experiment or survey. Small amounts of qualitative data used as an adjunct within a largely quantitative fixed-design study will not justify detailed and complex analysis. Often the need is simply to help the account be alive and communicate with the reader through an apt quotation or a telling example. But when the methods that generate qualitative data form a substantial part of the study or even determine it, one has to pay serious and detailed attention to the principles of qualitative data analysis. Two assumptions 1. If you have a substantial number of qualitative data, you will use a software package to deal with them. Standard software, even a simple word-processing package, can do much to reduce the sheer tedium of this operation (see Hahn, 2008 on the use of standard Microsoft Office software for a small qualitative project). For anything beyond a small number of data, it is of course essen- tial to use a computer. This will save you quite a lot of drudgery and will make you relate to the data with great ease. There are also specialist qualitative data analysis packages, which aid the process even more (see Appendix B for further details). 2. Unless you already have experience yourself, you will be helped or advised by someone who does have experience in this kind of analysis. In the past, the dominant model for it has been that of apprenticeship.
- Poul Rohleder, Antonia Lyons(Authors)
- 2017(Publication Date)
- Red Globe Press(Publisher)
286 COMBINING QUALITATIVE AND QUANTITATIVE DATA Table 16.2 Hypothetical data for a Q methodological design Q sort placement of item Alvi’s Q sort Dan’s Q sort Celia’s Q sort Q sort items 1. When I make choices about my +1 –4 –1 diabetes and health behaviour, I think through all the consequences of my actions. 2. I would rather leave the +4 –3 0 decisions to the experts and follow the advice they give. 3. I am especially worried about –2 0 –5 having injections. 4. Following a ‘diabetic lifestyle’ 0 +2 –2 (diet, exercise etc.) would spoil my pleasure in life. Traditional approaches: Social cognition Historically, health psychologists have turned to social cognition models for explanations, such as models of ‘reasoned action’, ‘planned behaviour’ and ‘stages of change’ (Prochaska & DiClemente, 1983). Quantitative research is used, generally based on questionnaires in which variables (such as ‘attitudes’, ‘normative beliefs’ and ‘social norms’) are manipulated to test the model in question. The problem is that these studies frequently fail to predict behaviour and fail to impress. As I commented some time ago: It is hardly surprising that you can predict fairly accurately what some-body will do if you ask them just before they do it whether they think doing it is a good idea, if they think other people will approve, and whether they care what other people think. … But getting consistent answers does not mean that you understand very much about their thinking except at a very trivial level, and then only under highly con-strained circumstances. (Stainton Rogers, 1991:53) More recently, Mielewczyk and Willig (2007) have criticized the whole social cognition approach more fundamentally, noting that most studies employ only one theoretical framework and thus one methodological approach.
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