Deck 13: Analysis of Qualitative Data

Question 1

Identify four differences between quantitative and qualitative data analysis. How is the process of conceptualization different between them?

Answer 1

Quantitative and qualitative data analysis are two different approaches to analyzing data, each with its own set of differences. Here are four key differences between the two:

1. Data Type: Quantitative data analysis deals with numerical data and focuses on statistical analysis and mathematical modeling, while qualitative data analysis deals with non-numerical data such as text, images, and videos, and focuses on interpreting and understanding the underlying meanings and patterns.

2. Research Design: Quantitative data analysis is often associated with a deductive research approach, where hypotheses are tested and relationships between variables are examined using structured research designs and standardized data collection methods. On the other hand, qualitative data analysis is often associated with an inductive research approach, where theories and concepts emerge from the data through open-ended and flexible data collection methods such as interviews, observations, and content analysis.

3. Analysis Techniques: Quantitative data analysis involves the use of statistical techniques such as regression analysis, t-tests, and ANOVA to analyze and interpret the data, while qualitative data analysis involves techniques such as thematic analysis, content analysis, and narrative analysis to identify patterns and themes within the data.

4. Generalizability: Quantitative data analysis aims to generalize findings to a larger population based on the sample data collected, while qualitative data analysis focuses on understanding the specific context and unique experiences of the participants without seeking generalizability.

The process of conceptualization is also different between quantitative and qualitative data analysis. In quantitative data analysis, conceptualization involves the development of clear and measurable variables and constructs that can be operationalized and tested using standardized measurement tools. In qualitative data analysis, conceptualization involves the exploration and interpretation of complex and nuanced concepts and phenomena, often through the development of rich and detailed descriptions and interpretations of the data. Overall, the process of conceptualization in quantitative data analysis is more structured and focused on measurement, while in qualitative data analysis it is more exploratory and focused on understanding the underlying meanings and experiences.

Question 2

How does a researcher code qualitative data? What are the three kinds of coding used by a qualitative researcher?

Answer 2

Qualitative data coding is a process used by researchers to analyze and categorize qualitative data in order to identify themes, patterns, and relationships within the data. There are three main kinds of coding used by qualitative researchers:

1. Open coding: This involves the initial process of breaking down the data into smaller segments and assigning labels or codes to these segments based on their content. This allows the researcher to identify and categorize different themes and concepts within the data.

2. Axial coding: This involves making connections between the codes identified during open coding. The researcher looks for relationships and patterns between the codes, and may reorganize and refine the coding structure to better capture the underlying meanings in the data.

3. Selective coding: This involves further refining and consolidating the codes to develop a comprehensive and coherent understanding of the data. The researcher identifies the core themes and concepts that emerge from the data and integrates them into a cohesive framework.

Overall, qualitative data coding is a systematic and iterative process that allows researchers to make sense of the rich and complex data collected through qualitative research methods. It helps to organize and interpret the data in a way that provides meaningful insights and contributes to the overall understanding of the research topic.

Question 3

Describe successive approximation. How is it similar to or different from ideal type analysis?

Answer 3

Successive approximation is a problem-solving method that involves making a series of small, incremental changes or adjustments to a solution in order to improve it over time. This approach is often used in engineering, mathematics, and computer science to find an optimal solution to a complex problem.

On the other hand, ideal type analysis is a sociological concept developed by Max Weber, which involves creating a theoretical model or idealized representation of a social phenomenon in order to understand and analyze it. Ideal type analysis is used in the social sciences to study and compare different social structures, institutions, and behaviors.

While both successive approximation and ideal type analysis involve creating models or representations of a phenomenon, they differ in their approach and purpose. Successive approximation focuses on practical problem-solving and iterative improvement, while ideal type analysis is more theoretical and abstract, aiming to understand and compare different social phenomena.

In summary, successive approximation is similar to ideal type analysis in that they both involve creating models or representations, but they differ in their approach and purpose, with successive approximation being more practical and problem-solving oriented, and ideal type analysis being more theoretical and abstract.

Question 4

What are the empty boxes in the illustrative method? How are they used?

Question 5

Explain the connection between conceptualization in qualitative research and qualitative data analysis, and contrast it with conceptualization and data analysis in quantitative research.

Question 6

Give an example of how qualitative researchers might use diagrams to help them analyze data.

Question 7

A researcher carefully followed ten nurses, one at a time, for four days. He recorded what each nurse did minute-by-minute and how long they spent on every activity. Afterwards, he examined how they really spent their time. He was conducting a(n)

A) time allocation analysis.
B) ideal type analysis.
C) matrix analysis.
D) successive approximation.
E) multiple sorting procedure.

Question 8

Talk about:
-axial coding

Question 9

Talk about:
-empty boxes

Question 10

Talk about:
-illustrative method

Question 11

Talk about:
-narrative

Question 12

Talk about:
-open coding

Question 13

Talk about:
-selective coding

Question 14

Talk about:
-successive approximation