Week 13

Question 1

what are the types of quantitative analysis, univariate

Answer 1

one variable

1. Frequency Distributions
   - percentage
2. Measures of Central Tendency
   - Mode, median, mean
3. Measures of Variations
   - range, percentiles-standard deviation (the average difference among individuals)

Question 2

what are the types of quantitative analysis, bivariate

Answer 2

(1) The Scattergram
(2) Bivariate Crosstabs
(3) Multivariate Crosstabs (three or more variables)

Question 3

explain scattergram

Answer 3

A diagram to display the statistical relationship between two variables based on plotting each case’s values for both of the variables

• A linear relationship (upward or downward), Positive or negative
• A curvilinear relationship (up and down or vice versa)

Question 4

explain bivariate crosstabs

Answer 4

(two variables)

Measure of Association-strength of association between two variables

Question 5

explain Multivariate Crosstabs

Answer 5

(three or more variables)
Statistical control -adding one or more control variable into the statistical model-building casual model (e.g., antecedent, intervening)

Question 6

explain quantitative statistical significance

Answer 6

Inferential statistics-Chi square test-Apply to univariate, bi-variate & multi-variate analysis
Generalizing the findings from the sample to the target population (external validity)

Question 7

what does qualitative analysis involve?

Answer 7

The Process of Knowledge Production

Question 8

what is the process of knowledge production?

Answer 8

• By developing themes, new concepts or abstract theories rather than testing theories (quantitative analysis)
• Conceptualization & Theory Building (after data collection), grounded in data (in comparison with Quantitative R)
• ideas supported by qualitative evidence

Question 9

what is the process of knowledge production?

Answer 9

• By developing themes, new concepts or abstract theories rather than testing theories (quantitative analysis)
• Conceptualization & Theory Building (after data collection), grounded in data (in comparison with Quantitative R)
• ideas supported by qualitative evidence

Question 10

what are the elements of knowledge production?

Answer 10

• Building materials: themes, codes, categories, classification
• Building methods: coding, memo writing, analytic induction, theory/concept building

Question 11

what is a code?

Answer 11

-a word or short phrase that symbolically assigns a summative, salient, essence-capturing and/or evocative attribute for a portion of language-based or visual data

Question 12

what is the purpose of coding?

Answer 12

-bring themes to the surface from deep inside the data

Question 13

Creating codes ?

Answer 13

-making sense of the data -assigning raw data with specific meaning

Question 14

Organizing codes

Answer 14

-creating different thematic drawers

Question 15

Types of Coding?

Answer 15

1. Open Coding
2. Axial Coding
3. Focused Coding

Question 16

explain Open Coding

Answer 16

(Line-by-line coding) – the initial rough stage

Read through your data to identify preliminary themes

Question 17

explain axial coding

Answer 17

linking codes
Understand the relationship between codes and derive new categories from codes
Compare codes to find consistencies and differences

Question 18

explain focused coding

Answer 18

Re-read your data to better organize these themes (group similar themes into broader ones, drop some that no longer seem important)

Question 19

explain analytic memo writing?

Answer 19

• Record of thoughts and ideas about the coding process
• Creates the link between raw data or evidence and formal theorizing and thesis statement creation
• “Theoretical Reflection”

Question 20

4 Strategies of Conceptual/Theoretical Development

Answer 20

Narrative approach – story telling
Ideal types
Successive approximation
Illustrative method

Question 21

explain the Narrative Approach?

Answer 21

Rely on codes to build the narrative
Concrete details presented in chronological order as if the product of a natural sequence of events
Data speak for themselves (grounded theory)
Valuing study participant’s voice and experiences

Question 22

explain Ideal Types – Theoretical Concept

Answer 22

,

Question 23

explain Ideal Types – Theoretical Concept

Answer 23

• Models or abstractions of social relations or processes (Weber)
• Help us to explain the social world (possible patterns)
• Compare ideal forms suggested by theory to empirical observations
• Note the ideal-reality difference
• Used for comparison, because no reality ever fits an ideal type.

Question 24

what are two aspects of ideal types?

Answer 24

1. Contrast contexts: Researchers with an interpretive approach use ideal types to interpret data in a way that is sensitive to the context and cultural meanings of members. The ideal type brings out the specifics of each case and can be used to emphasize the impact of the context. Thus, cases that dramatically contrast or that have distinctive features are often chosen.
2. Analogies: Used to organize qualitative data and facilitate logical comparisons. They make it easier to compare social processes across settings or cases. Do not provide a test of explanation but, instead, they guide the conceptual reconstruction of vast amounts of information and details into a systematic and sensible format.

Question 25

Successive Approximation – Theoretical Refinement

Answer 25

- Move back and forth between theory and data, until theory (or generalization) is maturely developed-a non-linear research process - Abstract concepts are rooted in concrete evidence and reflect the context - As the analysis progresses, the researcher refines generalizations and linkages to reflect the evidence better - Additional data is gathered during the theory building process and, over time, the evidence and theory begin to shape one another

Question 26

Illustrative Method

Answer 26

- Find empirical examples in the data (e.g., specific interview quotes) to support a theory - Theory provides empty boxes, and the researcher sees if the evidence can fill them - The evidence is used to confirm or reject theories

Question 27

Analytic Induction

Answer 27

- Look at an event and develop a thesis statement of what happened (the process of theory development) - Look at another similar event and see if it fits the thesis statement, If it doesn’t, revise the thesis statement - Look for exceptions to the thesis statement - When found, revise hypothesis to fit all examples encountered - Eventually, will develop a statement that accounts for all observed cases (context specific)

Question 28

similarities in quantitative and qualitative analysis?

Answer 28

Make inferences from data Faithful to the data Based on comparison

Question 29

differences of qualitative and quantitative analysis?

Answer 29

Less standardized Analysis begins earlier (often while in the field) Theory development, rather than testing More abstract Conceptualization Process (after data collection) Results of early analysis guides further data collection Because qualitative data takes the form of words rather than number, the data is less precise, context-specific, and can have multiple meanings and interpretations