Data Analysis Flashcards

1
Q

Analysis of Research Data

A
  • 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
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2
Q

Quantitative Data Analysis

A

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).

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3
Q

Qualitative Data Analysis

A

Qualitative data analysis does not require conversion into numbers unlike in quantitative research. It is more creative process to understand the experience

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4
Q

Transcription in Qualitative Research

A

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

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5
Q

Conversational Analysis

A

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
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6
Q

Discourse Analysis

A
  • 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
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7
Q

Narrative Analysis

A

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)
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8
Q

Grounded Theory

A
  • 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
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9
Q

Grounded Theory

A
  • 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.
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10
Q

Thematic Analysis

A
  • 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
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11
Q

Thematic Analysis

A
  • 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
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12
Q

6 Steps in Thematic Analysis

A
  1. Familiarize yourself with the data
  2. Generate initial codes
  3. Search for themes
  4. Reviewing themes
  5. Defining and naming themes
  6. Producing the report
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13
Q

Coding

A
  • 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
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14
Q

Coding

A
  • Line by line coding
  • Sentence by sentence
  • Several sentences
  • Paragraph by paragraph
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15
Q

Open Coding

A

the original conceptualization of the qualitative evidence into meaningful categories

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16
Q

Axial Coding

A

the re-examination of open coding in search of conceptual refinement and connections

17
Q

Selective Coding

A

the search of conceptual themes that link the conceptualized evidence into an integrated narrative

18
Q

Memoing

A

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
19
Q

What is Trustworthiness?

A

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

20
Q

Value of Trustworthiness

A

The value of a research study is strengthened by its trustworthiness.
Trustworthiness involves establishing:

  1. Credibility - confidence in the ‘truth’ of the findings. (Triangulation, member checking techniques)
  2. Transferability - showing that the findings have applicability in other contexts (by providing rich description)
  3. Dependability - showing that the findings are consistent and could be repeated (to show data to other researchers)
  4. 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.