How do films & TV shows influence our level of tolerance and respect towards cultural diversity and ethnicity? Analyze at least 5 TV shows and films
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Quantitative and Qualitative Data Analysis
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
WHY DO WE ANALYZE DATA
The purpose of analyzing data is to obtain usable and useful information. The analysis, irrespective of whether the data is qualitative or quantitative, may:
- Describe and summarize the data
- Identify relationships between variables
- Compare variables
- Identify the difference between variables
- Forecasts outcomes
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Scales of measurement
- It is important to figure out what type of analysis does a researcher use on her/his data and what the pictorial presentation or data display most suitable for a certain question..
- The decision is based on the scale of measurement of the data. These scales are nominal, ordinal and numerical
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Nominal scale
- is where the data can be classified into a non-numerical or named categories and the order in which these categories can be written or asked is arbitrary
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Numerical scale
- Where numbers represent the possible response categories
- There is a natural ranking of the categories
- Zero on the scale has a meaning
- There is a quantifiable difference within categories and between consecutive categories
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Ordinal scale
- Is where the data can be classified in non-numerical or named categories
- An inherent order exists within the response categories
- Ordinal scales in questions that call for
- Ratings of quality (for example very good, good, fair, poor, very poor)
- Agreement (Strongly agree, agree, neutral, disagree, strongly disagree)
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Common myths
- Complex analysis and big words impress people
- Analysis comes at the end after data is collected
- Quantitative data is more accurate
- Data have their own meaning
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Organizing the data
- Organize all forms/questionnaires in one place
- Check for completeness and accuracy
- Remove the incomplete forms; keep a record of your decisions
- Assign a unique identifier to each form /questionnaire
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Enter your data
- By hand
- By computer
- Excel (spreadsheet)
- Microsoft access (data management)
- Quantitative analysis :SPSS (statistical software)
- (count: frequencies, percentage, mean, mode, median, range, standard deviation, variance, ranking, cross tabulation)
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Interpreting Data
- Numbers don’t speak for themselves
- For example what does it mean that 25% of youth reported a change in behavior .. Or 55% of participated rather the program a 5 or 65% rated it a 4.
- What do these numbers mean
Interpretation is the process of attaching meaning to data
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
QUALITATIVE DATA ANALYSIS
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
Analyzing Qualitative Data
- Analysis
- Process of labeling and break down raw data
- Brings order, structure, interpretation
- Messy, ambiguous, time consuming
- Begins after first data collection
- Reflexive
- Inductive
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Choosing Analytic Method
- Sorting through a great deal of data is difficult
- Multiple plausible interpretations will be present
- The research question may have changed
- Still must remain true to participants’ meanings
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Analytical Memos
- Captures first impression and reflections
- Researcher writes memos to him or herself
- Not part of the data
- First attempt at analyzing
- Suggests avenues for additional collection or analytical schemes
- Researcher’s not participants’ evaluation
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Diagramming Data
- Place data into tables, diagrams, or graphs
- Helps see relationships
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Categorizing Data
- Reduces data into manageable size
- Category
- Set of similar excerpts, examples, or themes
- Existing or emergent
- Develop tentative labels
- Categories and labels will become
clearer over time - Return to the research questions
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Thematic Analysis
- Theme = conceptualization of interaction, relationship, event
- Three criteria
- Recurrence: same thread of meaning
- Repetition: explicit repetition of meanings
- Forcefulness
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Process of Interpretation
- Making sense or giving meaning to patterns, themes, concepts, and propositions
- Translating categories into meaningful whole
- Metaphoric frame
- Dramatistic frame
- Theoretical frame
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Evaluating Interpretation
- Do participant quotes illuminate the analysis?
- At least 3 examples
- Credibility
- Are findings believable?
- Are findings agreeable to participants?
- Triangulation
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
*
Chapter 16
Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved.
McGraw-Hill/Irwin
References
- http://www.uio.no/studier/emner/matnat/ifi/INF4260/h10/undervisningsmateriale/DataAnalysis.pdf
- https://people.uwec.edu/piercech/ResearchMethods/Data%20interpretation%20methods/data%20interpretation%20methods%20index.htm
*