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Descriptive Statistics

❶Focus Groups A focus group is a form of group interviewmainly used in marketing research.

Bridging Quantitative and Qualitative

Overcoming Challenges
Preparing Data
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A methods source book. Casting nets and testing specimens: Two grand methods of psychology. Conversational Analysis or CA is the study of naturally occurring talk-in-interaction, both verbal and non-verbal, in order to discover how we produce an orderly social world.

It does not refer to context or motive unless they are explicitly deployed in the talk itself. The method was inspired bythe ethnomethodology of Harold Garfinkel and further developed in the late s and early s by the sociologist Harvey Sacks.

Today CA is an established method used in sociology, anthropology, linguistics, speech-communication and psychology. Typically data are subjected to afine-grained sequential analysis based on a sophisticated form of transcription. In addition to sequential analysis, coding approaches have also been used in recent years for identifying recurrent themes.

The use of coding in conversational analysis however is questioned as an appropriate form of analysis by some. Ten Have, Paul A Practical Guide , Thousand Oaks: Making Thinking Visible with Atlas. Discourse Analysis DA and Critical Discourse Analysis CDA both encompass a number of approaches to study the world, society, events and psyche as they are produced in the use of language, discourse, writing, talk, conversation or communicative events. It is generally agreed upon that any explicit method in discourse studies, the humanities and social sciences may be used in CDA research, as long as it is able to adequately and relevantly produce insights into the way discourse reproduces or resists social and political inequality.

Thus, the data collection can be comprised of a number of different data formats. An example is provided by Graffigna and Bosio Textual Analysis for Social Research.

Fairclough, Norman; Clive Holes The Critical Study of Language. Graffigna, Guendalina and Bosio, A. International Journal of Qualitative Methods 5 3 , article 5.

Ethnography is a multi-method qualitative approachthat studies people in their naturally occurring settings. The purpose is to provide a detailed, in-depth description of everyday life and practice. An ethnographic understanding is developed through close exploration of several sources like participant observation, observation, interviews, documents, newspapers, magazine articles or artifacts.

The results of an ethnographic study are summaries of observed activities, typifications or the identification of patterns and regularities. Computer applications in qualitative research. Qualitative Social Research, 8 3 , Art. Qualitative Social Research, 10 2 , Art. The founder of Ethnomethodology Harold Garfinkel , developed this methodto better understand the social order people use in making sense of the world through.

As data sources he uses accounts and descriptions of day-to-day experiences. The aim is to discover the methods and rules of social action that people use in their everyday life. The focus is on how-question, rather than why-question as underlying motives are not of interest. Ethnomethodologists conduct their studies in a variety of ways focusing on naturally occurring data.

Central is the immersion in the situation being studied. They reject anything that looks like interview data. Important for an ethnomethodological analysis is self-reflection and the inspectability of data, thus the reader of an ethnomethodological study should be able to inspect the original data as means to evaluate any claim made by the analyst.

Steps in the process of data analysis include coding by type of discourse, counting frequencies of types of discourses, selecting the main types and checking for deviant cases. Francis, David and Stephen Hester. An invitation to Ethnomethodology. Language, Society and Interaction. Its methodological roots are in phenomenology, social interactionism and ethnographyadapted by business studies and marketing research, but also used in other disciplines like medical research. The investigation is carried out in the naturalistic environment where the phenomenon occurs.

Methods of data collection include participant observation, depth interviews, group interviews and projective techniques. Analysis procedures consist of description, ordering or coding of data and displaying summaries of the data. Gendered Suffering and Social Transformations: Domestic Violence, Dictatorship and Democracy in Chile. A focus group is a form of group interviewmainly used in marketing research. A Practical Guide for Applied Research, 3rd ed. The focused interview and the focus group — continuities and discontinuities.

Public Opinions Quarterly, 51, A manual of problems and procedures. Frame Analysis has generally been attributed to the work of Erving Goffman and his book: An essay on the organization of experience. This approach tries to explain social phenomena in terms of the everyday use of schemes or frames like beliefs, images or symbols. The number of such frames available to people in making sense of their environment is limited by the particular society they live in.

Frame Analysis is largely used in social movement theory, policy studies and health research. When it comes to analyzing the data, a quantitative and a qualitative approach has been suggested. In quantitative studies the keyword approach is used extracting frames by means of hierarchical cluster or factor analysis.

The software VBPro for example has especificallybeen developed for such procedures. Frames may however also be discovered via a qualitative coding approach. Propaganda Plays of the Woman Suffrage Movement: An Essay on the Organization of Experience. Media Coverage on European Governance: European Journal of Communication 19 3 Grounded Theory GT is an inductive form of qualitative research that was first introduced by Glaser and Strauss It is a research approach in which the theory is developed from the data, rather than the other way around.

Data collection and analysis are consciously combined, and initial data analysis is used to shape continuing data collection. Strauss in disagreement with Glaser developed the approach further providing a more pragmatic and systematic descriptions of analytic steps, like the four different phases of coding: Sociological research has been greatly influenced by Grounded Theory and the method of coding based constant comparison and the theoretical sampling strategy is widely accepted.

In recent years, further variations of the grounded theory methodology have emerged. For example Kathy Charmaz introduced a constructivist version and Clarke discusses GT after the postmodern turn.

Glaser rubbish the use of tape recording and transcription as he considers it a superfluous activity not aiding the process of conceptualizing.

Consequently he advises against the use of software. See a few examples below. Grounded Theory After the Postmodern Turn. Discovery of Grounded Theory: Strategies for Qualitative Research. Basics of Grounded Theory Analysis: Qualitative Analysis for Social Scientists. Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory. Burden, Johann and Roodt, Gert Grounded theory and its application in a recent study on organizational redesign.

Some reflections and guidelines. Journal of Human Resource Management, 5 3 , 11 — Qualitative Social Research, 1 1 , Art.

Inferential statistics allow the researcher to begin making inferences about the hypothesis based on the data collected. This means that, while applying inferential statistics to data, the researcher is coming to conclusions about the population at large.

Inferential statistics seek to generalize beyond the data in the study to find patterns that ostensibly exist in the target population. This course will not address the specific types of inferential statistics available to the researcher, but a succinct and very useful summary of them, complete with step-by-step examples and helpful descriptions, is available here. Conducting Research in Psychology: Measuring the Weight of Smoke, 3rd Edition. Wadsworth Publishing February 27, All Rights Reserved Worldwide.

Privacy Policy Information Disclaimer. Data Preparation and Analysis Preparing Data After data collection, the researcher must prepare the data to be analyzed.

This means that for the most part, if a person is tall, they are likely to have a large shoe size, and conversely, if they are short, they are likely to have a smaller shoe size. Thus, we use inferential statistics to make inferences from our data to more general conditions; we use descriptive statistics simply to describe what's going on in our data. In most research studies, the analysis section follows these three phases of analysis.

Descriptions of how the data were prepared tend to be brief and to focus on only the more unique aspects to your study, such as specific data transformations that are performed. The descriptive statistics that you actually look at can be voluminous. In most write-ups, these are carefully selected and organized into summary tables and graphs that only show the most relevant or important information. Usually, the researcher links each of the inferential analyses to specific research questions or hypotheses that were raised in the introduction, or notes any models that were tested that emerged as part of the analysis.

In most analysis write-ups it's especially critical to not "miss the forest for the trees.

Analysis is more than coding

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Quantitative Data Analysis Resources The Rice Virtual Lab in Statistics also houses an online textbook, Hyperstat. This textbook introduces univariate and bivariate analysis, probability, distribution and hypothesis testing.

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Methodology chapter of your dissertation should include discussions about the methods of data analysis. You have to explain in a brief manner how you are going to analyze the primary data you will collect employing the methods explained in this chapter.

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By the time you get to the analysis of your data, most of the really difficult work has been done. It's much more difficult to: define the research problem; develop and implement a sampling plan; conceptualize, operationalize and test your measures; and develop a design structure. Qualitative data refers to non-numeric information such as interview transcripts, notes, video and audio recordings, images and text documents. Qualitative data analysis can be divided into the following five categories: 1. Content analysis. This refers to the process of categorizing verbal or.

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15 Methods of Data Analysis in Qualitative Research Compiled by Donald Ratcliff 1. Typology - a classification system, taken from patterns, themes, or other kinds of. Module 5: Data Preparation and Analysis Preparing Data. After data collection, the researcher must prepare the data to be analyzed. Organizing the data correctly .