Quantitative and Qualitative Data
Analysis
Lecture 1: Introduction
Dr. Engr. Sami ur Rahman
Reference books
 Statistics (3rd Ed.) by David Freedman, Robert Pisani
and Roger Purves. Norton
 Doing Data Analysis with SPSS Version 12 by Carver
and Nesh.
 Qualitative Data Analysis: An Expanded Sourcebook, by
Matthew B. Miles and A. Michael Huberman. 2nd Edition.
Sage Publications: Thousand Oaks, CA
 A Practical Guide to Scientific Data Analysis by David
Livingstone ChemQuest, Sandown, Isle of Wight, UK
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 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 | 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 | 4
Data
Data: Values of qualitative or quantitative variables.
Student No
Hours Studied
Marks
1
1
40
2
4
80
3
2
50
4
4
70
5
5
90
6
3
60
7
2
45
8
1
42
9
4
85
10
3
70
What information do we get from this data??
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 5
Data Analysis
Student
No
1
2
3
4
5
6
7
8
9
10
Hours
Studied
1
4
2
4
5
3
2
1
4
3
Marks
40
80
50
70
90
60
45
42
85
70
Sorted data
Student Hours
No
Studied Marks
1
1
40
8
1
42
3
2
50
7
2
45
6
3
60
10
3
70
2
4
80
4
4
70
9
4
85
5
5
90
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 6
Data Presentation
100
Marks
40
42
50
45
60
70
80
70
85
90
90
90
85
80
80
70
70
Marks
Student Hours
No
Studied
1
1
8
1
3
2
7
2
6
3
10
3
2
4
4
4
9
4
5
5
60
70
60
50
50
Series1
45
42
40
40
30
20
10
0
0
1
2
3
4
5
6
Hours studied
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 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
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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 | 9
Types of Data Analysis
Quantitative Data Analysis:
Converting quantitative data into information
Qualitative Data Analysis:
Converting qualitative data into information
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Quantitative Analysis
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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.
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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?
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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
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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"
Central Tendency
Average (Mean)
Median
Mode
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Mean
Mean (arithmetic mean) of data values
n
X
X
i 1
n
i
X1  X 2 

n
 Xn
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Mean
 The most common measure of central tendency
 Affected by extreme values (outliers)
0 1 2 3 4 5 6 7 8 9 10
Mean = 5
0 1 2 3 4 5 6 7 8 9 10 12 14
Mean = 6
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 17
Median
Median: The “middle” number
Not affected by extreme values
0 1 2 3 4 5 6 7 8 9 10
0 1 2 3 4 5 6 7 8 9 10 12 14
Median = 5
Median = 5
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 18
Mode
Mode: Value that occurs most often
 Not affected by extreme values
 There may be no mode
 There may be several modes
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
0 1 2 3 4 5 6
No Mode
Mode = 9
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 19
Simple quantitative analysis
Graphical representations give overview of data
Number of errors made
Number of errors made
10
8
6
4
2
0
0
5
10
15
20
User
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 20
Simple quantitative analysis
Graphical representations give overview of data
Internet use
< once a day
once a day
once a week
2 or 3 times a week
once a month
University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 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 | 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 | 23
Qualitative Analysis
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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 | 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 | 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 | 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 | 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 | 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 | 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 | 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?
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Thanks for your attention
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