1. Research Methods in Computer Science Lecture: Quantitative and Qualitative Data Analysis
| Department of Science | Interactive Graphics System (GRIS) | Prof. Dr. techn. Dieter Fellner

2. Outline Motivation What is Data? What is Data Analysis
Quantitative Data and Qualitative Data
Quantitative and Qualitative Data Analysis
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 2
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

3. Things aren’t always what we think!
Blind men and an elephant
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 3
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

4. Data Data: Values of qualitative or quantitative variables. Student No
Hours Studied
Marks 1 40 2 4 80 3 50 70 5 90 6 60 7 45 8 42 9 85 10
Data: Groups of observations are called data, which may be qualitative or quantitative.
What information do we get from this data??
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 4
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

5. Data Analysis Sorted data Student No Hours Studied Marks 1 40 2 4 80 350 70 5 90 6 60 7 45 8 42 9 85 10
Student No
Hours Studied
Marks 1 40 8 42 3 2 50 7 45 6 60 10 70 4 80 9 85 5 90
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 5
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

6. Student No Hours Studied Marks
Data Presentation
Student No
Hours Studied
Marks 1 40 8 42 3 2 50 7 45 6 60 10 70 4 80 9 85 5 90
Marks
Hours studied
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 6
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

7. What is data analysis?
Data analysis is the process of turning data into information
An attempt by the researcher to summarize collected data
Data Interpretation is an attempt to find meaning
Good analysis communicates something meaningful about the world
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 7
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

8. Types of Data Quantitative Data:
Data that is numerical, counted, or compared on a scale
Qualitative Data:
Textual data
Interview transcripts
Case notes/ clinical notes
Photographs
Video recordings
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 8
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

9. Types of Data Analysis Quantitative Data Analysis:
Converting quantitative data into information
Qualitative Data Analysis:
Converting qualitative data into information
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 9
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

10. Quantitative Analysis
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 10
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

11. Quantification of Data
Quantification Analysis : The numerical representation and manipulation of observations for the purpose of describing and explaining the phenomena that those observations reflect.
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 11
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

12. Quantitative Analysis
Can be used to answer questions like
What is the percent distribution?
How much variability is there in the data?
Are the results statistically significant?
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 12
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

13. Simple Quantitative Analysis
Averages
Mean: add up values and divide by number of data points
Median: middle value of data when ranked
Mode: figure that appears most often in the data
Percentages
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 13
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

14. Central Tendency Central Tendency
Central tendency: The way in which quantitative data tend to cluster around some value. A measure of central tendency is any of a number of ways of specifying this "central value"
Median
Mode
Central Tendency
Average (Mean)
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 14
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

15. Mean Mean (arithmetic mean) of data values
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 15
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

16. Mean The most common measure of central tendency
Affected by extreme values (outliers)
Mean = 6
Mean = 5
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 16
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

17. Median Median: The “middle” number Not affected by extreme values
Median = 5
Median = 5
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 17
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

18. Mode Mode: Value that occurs most often Not affected by extreme values
There may be no mode
There may be several modes
Mode = 9
No Mode
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 18
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

19. Simple quantitative analysis
Graphical representations give overview of data
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 19
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

20. Simple quantitative analysis
Graphical representations give overview of data
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 20
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

21. Strengths of Quantitative Research
Precise, quantitative, numerical data
Testing hypothesis/confirming theories
Generalizing finding, random samples with sufficient size
Comparatively quick data collection
Less time consuming analysis
May minimize personal bias .
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 21
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

22. Weaknesses of Quantitative Research
Only applicable for measurable (quantifiable) phenomena
Simplifies and ”compresses” the complex reality, lack of detailed narrative
Theories or categories might not reflect local constituencies’ understandings
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 22
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

23. Qualitative Analysis
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 23
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

24. Qualitative Data Narratives, logs, experience Interviews
Diaries and journals
Notes from observations
Photographs
Video recordings
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 24
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

25. What is Qualitative Research?
Research studies that investigate the quality of
Relationships
Activities
Situations
Materials
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 25
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

26. Qualitative Data Analysis
Used for any non-numerical data collected as part of the evaluation
Unstructured observations
Analysis of written documents
Diaries, observations
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 26
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

27. Qualitative Data Analysis
Answers questions like:
Is the project being implemented according to plan?
What are some of the difficulties faced by staff?
Why did some participants drop out early?
What is the experience like for participants?
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 27
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

28. Steps in Qualitative Research
The steps are as follows (in some cases):
Identification of the phenomenon and hypothesis generation
Identification of the participants in the study
Data collection (continual observance)
Data analysis
Interpretation/Conclusions
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 28
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

29. Generalization in Qualitative Research
A generalization is usually thought of as a statement or claim that applies to more than one individual, group, or situation.
The value of a generalization is that it allows us to have expectations about the future.
A limitation of Qualitative Research is that there is seldom justification for generalizing the findings of a particular study.
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 29
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

30. Trustworthiness in Qualitative Research
Check on the trustworthiness of the researchers:
Compare one informant’s description with another informant’s description of the same thing.
Triangulation: Comparing different information on the same topic.
Data triangulation
Use of multiple data sources
Students, teachers, administrators, etc.
Methods triangulation
Interviews, observations, etc.
Researcher triangulation
Use a team of researchers.
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 30
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

31. Criteria for judging research
Quantitative
Internal validity
Did A cause B?
External Validity
Are these findings generalizable?
Reliability
Are the measures repeatable?
Objectivity
Are the findings free of researcher bias/values?
Qualitative
Credibility
Believable from participant’s view
Transferability
Can this finding be transferred to other contexts?
Dependability
Would another researcher come to similar conclusions?
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 31
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

32. Grounded Theory
University Of Malakand | Department of Computer Science | Visual Computing Research Group | Dr. Engr.Sami ur Rahman | 32

33. Grounded Theory Definition
The discovery of theory from data – systematically obtained and analyzed in social research’ (Glaser & Strauss, 1967)
The purpose of using Grounded Theory method is to develop a theory from the data being examined (theory fits what is seen in the data)
The purpose of Grounded Theory is to explain the data (concepts)
University Of Malakand | Department of Computer Science | Visual Computing Research Group | Dr. Engr.Sami ur Rahman | 33

34. Why use Grounded Theory?
You may be in an area where there is little or no theory in existence.
You may not agree with existing theories.
University Of Malakand | Department of Computer Science | Visual Computing Research Group | Dr. Engr.Sami ur Rahman | 34

35. Disadvantages of Grounded Theory
Difficult to gain funding, as each project has no specific beginning or end.
A relatively young and developing method.
It is not developed to test hypotheses.
Inadequate for comparing two theses.
Can be inadequate for projects with specific aims, such as evaluations.
University Of Malakand | Department of Computer Science | Visual Computing Research Group | Dr. Engr.Sami ur Rahman | 35

36. Thanks for your attention
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 36
| Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner