Skip Nav

Data Analysis: Techniques & Methods

You must create an account to continue watching

❶Take quizzes and exams. How to Evaluate a Marketing Plan.

Sign Up for Newsletter

Analysis is more than coding
A Beginning Look at Data Analysis
404 - File or directory not found.

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. The grounded theory method and case study data in IS research: The Creation of Theory: As a theory of interpretation, the hermeneutic tradition stretches all the way back to ancient Greek philosophy. In the middle ages and the Renaissance, hermeneutics emerges as a method to identify the meaning and intent of Biblical scripture. Today hermeneutics is also used as a strategy to address a broad range of research questions like interpreting human practices,events, and situations.

Researchers bring their personal conviction to the analysis, but they need to be open for revision. In the process of collecting data, a tentative understanding is developed which is then tested against reality.

Further understanding is gained if discrepancies between the current interpretation and the new data are recognized. Thus, the process of understanding is characterized by constant revisions. This is referred to as the hermeneutic cycle. Research Methods for Political Science: Quantitative and Qualitative Methods.

Wallach, Harald , 2. Psychologie — Wissenschaftstheorie, philosophische Grundlagen und Geschichte: The term originally comes from phenomenological sociology, where it refers to the familiar world of everyday life. In analyzing lifeworlds, one attempts to draw out the individual structures within it. A lifeworld can be understood as a physical environment even though the various inhabitants do not necessarily attribute the same meaning to the same space.

Cats and people for example may inhabit the same physical environment but live in different lifeworlds as cupboards, window sills, and spaces underneath chairs have different significances for both of them. The aim is the reconstruction of the various subjective perspectives.

The trick is to determine the right size for a sample to be accurate. Using proportion and standard deviation methods, you are able to accurately determine the right sample size you need to make your data collection statistically significant.

When studying a new, untested variable in a population, your proportion equations might need to rely on certain assumptions. However, these assumptions might be completely inaccurate. This error is then passed along to your sample size determination and then onto the rest of your statistical data analysis. Also commonly called t testing, hypothesis testing assesses if a certain premise is actually true for your data set or population.

Hypothesis tests are used in everything from science and research to business and economic. To be rigorous, hypothesis tests need to watch out for common errors. For example, the placebo effect occurs when participants falsely expect a certain result and then perceive or actually attain that result.

Another common error is the Hawthorne effect or observer effect , which happens when participants skew results because they know they are being studied. However, avoiding the common pitfalls associated with each method is just as important. Let's look at some of the techniques:.

The goal of a survey is to gather responses from the participants through questions. For your assignment about school systems, you might mail out a survey to the teachers at both public and private schools. This will allow you to gather the different perspectives from each type of school. Tracking involves tracking the behavior or actions of participants.

A great example of this are websites that track customers that visit their sites. Experiments can be customized for the type of research product. They are a way to test some factor. An example might be taking children from a public school and placing them in a private school for a day.

Data analysis has two prominent methods: Each method has their own techniques. Interviews and observations are forms of qualitative research, while experiments and surveys are quantitative research. To unlock this lesson you must be a Study. Did you know… We have over college courses that prepare you to earn credit by exam that is accepted by over 1, colleges and universities. You can test out of the first two years of college and save thousands off your degree.

Anyone can earn credit-by-exam regardless of age or education level. To learn more, visit our Earning Credit Page. Not sure what college you want to attend yet? The videos on Study. Students in online learning conditions performed better than those receiving face-to-face instruction. By creating an account, you agree to Study. Explore over 4, video courses. Find a degree that fits your goals. We'll define the two methods of data analysis, quantitative and qualitative, and look at each of their various techniques.

The lesson will then conclude with a summary and a quiz. Start Your Free Trial Today. An error occurred trying to load this video. Try refreshing the page, or contact customer support. You must create an account to continue watching. Register for a free trial Are you a student or a teacher? I am a student I am a teacher. It only takes a few minutes to set up and you can cancel at any time. What teachers are saying about Study. What is Data Analytics? Are you still watching?

Your next lesson will play in 10 seconds. Add to Add to Add to. Want to watch this again later? Factors That Influence Customer Loyalty. What is Data Analysis? Importance of Training in the Hospitality Industry.

Path to Competitive Advantage. How to Evaluate a Marketing Plan. Steps in the Material Requirements Planning Process. Limits to Generalization of a Research Study. Effective Communication in the Workplace: UExcel Workplace Communications with Computers: TExES Mathematics High School Algebra I: Holt McDougal Algebra 2: High School Algebra II: In this lesson, we'll learn about data analysis.

A Beginning Look at Data Analysis Let's imagine that you have just enrolled in your first college course. Methods of Data Analysis Okay, you have decided to prove that public school is better than private school, but now you need to figure out how you will collect the information and data needed to support that idea.

Qualitative Data Analysis Techniques Qualitative research works with descriptions and characteristics. Let's look at some of the more common qualitative research techniques: Want to learn more? Select a subject to preview related courses: Quantitative Data Analysis Techniques Quantitative research uses numbers.

Main Topics

Privacy Policy

Data Analysis 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.

Privacy FAQs

A source of confusion for many people is the belief that qualitative research generates just qualitative data (text, words, opinions, etc) and that quantitative research generates just quantitative data (numbers).

About Our Ads

Data analysis has two prominent methods: qualitative research and quantitative research. Each method has their own techniques. Each method has their own techniques. Interviews and observations are forms of qualitative research, while experiments and surveys are quantitative research. My e-book, The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step approach contains a detailed, yet simple explanation of quantitative data analysis methods. The e-book explains all stages of the research process starting from the selection of the research area to writing personal reflection.

Cookie Info

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 groups of data. (Patton pp. ,) John Lofland & Lyn Lofland Ideally, categories should be mutually exclusive and exhaustive if possible, often they aren't. In qualitative research, you are either exploring the application of a theory or model in a different context or are hoping for a theory or a model to emerge from the data.