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Qualitative Research
Qualitative research is an umbrella term for an array of attitudes toward and strategies for conducting inquiry that are aimed at discerning how human beings understand, experience, interpret, and produce the social world (Mason, 1996). Although typically juxtaposed with quantitative research, qualitative research is not a unified form of inquiry clearly differentiated from it, but rather home to a variety of scholars from the sciences, humanities, and practice disciplines committed to different and, sometimes, conflicting philosophical and methodological positions.
These philosophical positions include, but are not limited to, interpretivism, hermeneutics, social constructionism, and critical theory, as these are variously defined. Methodologic approaches include, but are not limited to, phenomenology, grounded theory, ethnography, participatory inquiry, and narrative and discourse analysis, as these are variously defined (Denzin & Lincoln, 2000a). History, literary criticism, ethics, and cultural and material culture studies are examples of disciplines often viewed as wholly defined by qualitative research. Yet demographic history, for example, is largely quantitative, and scholars in these fields do not typically refer to themselves as qualitative researchers or to their work as qualitative research, or even as research at all. Qualitative researchers in the social sciences have turned to the arts and humanities to learn how to read and perform texts like artists and humanists, whereas qualitative researchers in the humanities have turned to the social sciences to learn how to theorize and conduct fieldwork like social scientists (Denzin & Lincoln, 2000b). In short, qualitative research is a term that tends to obscure both difference and commonality. Qualitative research cannot be understood and, indeed, is often misunderstood and misrepresented by simply contrasting it with quantitative research, which is, in turn, similarly misrepresented by efforts to reduce its diversity and complexity.
Qualitative Research versus Qualitative Data and Techniques
What is collectively referred to as qualitative research should be distinguished from other research and other works that merely contain qualitative data, such as descriptive survey studies and journalistic accounts, and from data collection and analysis techniques commonly viewed as qualitative research techniques, such as focus groups and content analysis. Both focus groups and content analysis have their origins in, and are still widely used in, quantitative research. That is, there is no qualitative attitude or strategy necessarily inherent in these techniques. Moreover, all quantitative behavioral and social science research with human subjects depends on qualitative data in the questionnaires employed. The mere fact that words are used or produced in a project, or that words prevail over numbers, does not make a work qualitative research, just as the mere fact that numbers are used or produced in a project does not make a work quantitative research.
Defining Features of Qualitative Research
What makes a work deserving of the label qualitative research is the demonstrable effort to produce richly and relevantly detailed descriptions and particularized interpretations of people and the social, linguistic, material, and other practices and events that shape and are shaped by them. Qualitative research typically includes, but is not limited to, discerning the perspectives of these people, or what is often referred to as the actor’s point of view. Although both philosophically and methodologically a highly diverse entity, qualitative research is marked by certain defining imperatives that include its case (as opposed to its variable) orientation, sensitivity to cultural and historical context, and reflexivity. In its many guises, qualitative research is a form of empirical inquiry that typically entails some form of purposive sampling for information-rich cases; in-depth interviews and open-ended interviews, lengthy participant/field observations, and/or document or artifact study; and techniques for analysis and interpretation of data that move beyond the data generated and their surface appearances. Qualitative research is typically directed toward producing idiographic (as opposed to nomothetic) knowledge because its emphasis is on the penetrating understanding of particular phenomena, events, or cases.
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- Analysis of Variance
- Association and Correlation
- Association
- Association Model
- Asymmetric Measures
- Biserial Correlation
- Canonical Correlation Analysis
- Correlation
- Correspondence Analysis
- Intraclass Correlation
- Multiple Correlation
- Part Correlation
- Partial Correlation
- Pearson's Correlation Coefficient
- Semipartial Correlation
- Simple Correlation (Regression)
- Spearman Correlation Coefficient
- Strength of Association
- Symmetric Measures
- Basic Qualitative Research
- Basic Statistics
- F Ratio
- N(n)
- t-Test
- X¯
- Y Variable
- z-Test
- Alternative Hypothesis
- Average
- Bar Graph
- Bell-Shaped Curve
- Bimodal
- Case
- Causal Modeling
- Cell
- Covariance
- Cumulative Frequency Polygon
- Data
- Dependent Variable
- Dispersion
- Exploratory Data Analysis
- Frequency Distribution
- Histogram
- Hypothesis
- Independent Variable
- Measures of Central Tendency
- Median
- Null Hypothesis
- Pie Chart
- Regression
- Standard Deviation
- Statistic
- Causal Modeling
- Discourse/Conversation Analysis
- Econometrics
- Epistemology
- Ethnography
- Evaluation
- Event History Analysis
- Experimental Design
- Factor Analysis and Related Techniques
- Feminist Methodology
- Generalized Linear Models
- Historical/Comparative
- Interviewing in Qualitative Research
- Latent Variable Model
- Life History/Biography
- Log-Linear Models (Categorical Dependent Variables)
- Longitudinal Analysis
- Mathematics and Formal Models
- Measurement Level
- Measurement Testing and Classification
- Multilevel Analysis
- Multiple Regression
- Qualitative Data Analysis
- Sampling in Qualitative Research
- Sampling in Surveys
- Scaling
- Significance Testing
- Simple Regression
- Survey Design
- Time Series
- ARIMA
- Box-Jenkins Modeling
- Cointegration
- Detrending
- Durbin-Watson Statistic
- Error Correction Models
- Forecasting
- Granger Causality
- Interrupted Time-Series Design
- Intervention Analysis
- Lag Structure
- Moving Average
- Periodicity
- Serial Correlation
- Spectral Analysis
- Time-Series Cross-Section (TSCS) Models
- Time-Series Data (Analysis/Design)
- Trend Analysis
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