Data Analysis Flashcards
Analysis of Research Data
- Is a process of cleaning, transforming, and modeling data to discover useful information
- Data analysis is the process of converting the raw data into information
- The process that helps in reducing a large chunk of data into smaller fragments
- A mass of collected data could be brought to order, structure and meaning
- It could be messy, ambiguous, and time-consuming process, however, at the same time, it could creative process too
Quantitative Data Analysis
Quantitative data analysis converts social science data into a form that could be read and manipulated through the computer programs and could be statistically analyzed (ex. SPSS, STRATA, etc).
Qualitative Data Analysis
Qualitative data analysis does not require conversion into numbers unlike in quantitative research. It is more creative process to understand the experience
Transcription in Qualitative Research
Most used types of transcriptions in qualitative research:
Verbatim transcription
- Records all interactions and signs of emotions (coughs, sighs, laughs, speaking softly etc.) and filler words as uh, em, er, ah, hmm, you know, I mean, sort of, etc.
Word-for-word transcription
- Captures the text as it is spoken but eliminate all filler words
Conversational Analysis
CA – is the search to understand the basic structures of social interaction and social order through the detailed study of everyday talk
- Conversation is socially constructed – its includes established rules and behaviours that could be analyzed
- Conversations are established within the context and it is necessary to understands the context too
- CA analysis looks to the the structures of conversations, including pauses, emotions, etc
Discourse Analysis
- Examines text to explore how meaning, knowledge and power are created and recreated in everyday experiences
- A critical approach for taken for granted knowledge
- Searches for thematic patterns and seeks to improve understanding of how language works in its social and cultural contexts
Narrative Analysis
Strategies for analyzing text that focus how people use stories to make sense of themselves, their experiences and the world
Three dimension approach:
- Interaction (personal and social)
- Continuity (past, present and future)
- Situation (a physical places or the storyteller’s places)
Grounded Theory
- Moves beyond description and discovers the theory for a specific goal: process or action
- Philosophy behind – theory development ‘grounded’ in data from participants
- Inductive approach – discovering theory – generate theory from data
- Not verifying the existing theories but developing new, produce new explanation to specific process/problem
Grounded Theory
- Start with no preconceptions – ‘bracket’ your knowledge to influence theory construction
- Analysis and data collection can go together
- Constant comparative method – requires comparison of places, settings, conditions, people, events, relationships etc.
Thematic Analysis
- Provides core skills for doing qualitative analysis – ‘thematizing meaning’
- Is a method for identifying, analysing and reporting patterns/themes within the data
- Search for certain themes/patterns across an entire data set
- Researcher makes the decisions and identifies the patterns and themes
Thematic Analysis
- A theme captures something important about the data in relation to research question, and represents some level of patterned response
- How to identify the representation of the theme, if it does not provide quantifiable measure?
- Based on researcher’s judgement
- Analytic process involves a progression from description: demonstrates and summarizes patterns
6 Steps in Thematic Analysis
- Familiarize yourself with the data
- Generate initial codes
- Search for themes
- Reviewing themes
- Defining and naming themes
- Producing the report
Coding
- Process of organizing and sorting your data
- Codes serve as a way to label, compile and organize your data
- Allow you to summarize and synthesize what is happening in your data
Coding
- Line by line coding
- Sentence by sentence
- Several sentences
- Paragraph by paragraph
Open Coding
the original conceptualization of the qualitative evidence into meaningful categories
Axial Coding
the re-examination of open coding in search of conceptual refinement and connections
Selective Coding
the search of conceptual themes that link the conceptualized evidence into an integrated narrative
Memoing
Consists of writing notes to yourself while you are reading and rereading your data, and/or analyzing data
- These notes are your initial ideas about the patterns and connections you are discovering
- Code Notes, Theoretical notes, Operational notes
What is Trustworthiness?
How can the inquirer persuade their audiences (including self) that the findings of an inquiry are worth paying attention to and worth taking account of
Value of Trustworthiness
The value of a research study is strengthened by its trustworthiness.
Trustworthiness involves establishing:
- Credibility - confidence in the ‘truth’ of the findings. (Triangulation, member checking techniques)
- Transferability - showing that the findings have applicability in other contexts (by providing rich description)
- Dependability - showing that the findings are consistent and could be repeated (to show data to other researchers)
- Confirmability - a degree of neutrality OR the extent to which the findings of a study are shaped by the respondents and not researcher bias, motivation, or interest.
