Quantitative and Qualitative Data Analysis Lecture 1: Introduction

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Quantitative and Qualitative Data Analysis Lecture 1: Introduction

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Quantitative and Qualitative Data Analysis Lecture 1: Introduction

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Quantitative and Qualitative Data AnalysisLecture 1: Introduction

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 2

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 | 3

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 | 4

Blind men and an elephant

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 5

Data: Values of qualitative or quantitative variables.

What information do we get from this data??

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 6

Sorted data

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 7

Marks

Hours studied

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 8

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 | 9

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 | 10

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 | 11

Quantitative Analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 12

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 | 13

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 | 14

- 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 | 15

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

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 16

- Mean (arithmetic mean) of data values

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 17

- The most common measure of central tendency
- Affected by extreme values (outliers)

0 1 2 3 4 5 6 7 8 9 10

0 1 2 3 4 5 6 7 8 9 10 12 14

Mean = 5

Mean = 6

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 18

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 | 19

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 | 20

- Graphical representations give overview of data

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 21

- Graphical representations give overview of data

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 22

- 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 | 23

- 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 | 24

Qualitative Analysis

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 25

- 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 | 26

- Research studies that investigate the quality of
- Relationships
- Activities
- Situations
- Materials

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 27

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 | 28

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 | 29

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 | 30

- 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 | 31

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.

- Use of multiple data sources
- Methods triangulation
- Interviews, observations, etc.

- Researcher triangulation
- Use a team of researchers.

- Data triangulation

University Of Malakand | Department of Computer Science | UoMIPS| Dr. Engr. Sami ur Rahman | 32

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 | 33

Thanks for your attention