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Dr. Engr. Sami ur Rahman Quantitative and Qualitative Data Analysis Lecture 1: Introduction.

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Presentation on theme: "Dr. Engr. Sami ur Rahman Quantitative and Qualitative Data Analysis Lecture 1: Introduction."— Presentation transcript:

1 Dr. Engr. Sami ur Rahman Quantitative and Qualitative Data Analysis Lecture 1: Introduction

2 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 Reference books

3 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 3 Outline  Motivation  What is Data?  What is Data Analysis  Quantitative Data and Qualitative Data  Quantitative and Qualitative Data Analysis

4 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 4 Things aren’t always what we think! Blind men and an elephant

5 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 5 Data Student NoHours StudiedMarks 1140 2480 3250 4470 5590 6360 7245 8142 9485 10370 What information do we get from this data?? Data: Values of qualitative or quantitative variables.

6 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 6 Data Analysis Student No Hours StudiedMarks 1140 2480 3250 4470 5590 6360 7245 8142 9485 10370 Student No Hours StudiedMarks 1140 8142 3250 7245 6360 10370 2480 4470 9485 5590 Sorted data

7 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 7 Data Presentation Student No Hours StudiedMarks 1140 8142 3250 7245 6360 10370 2480 4470 9485 5590 Marks Hours studied

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

9 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 Types of Data

10 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 Types of Data Analysis

11 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 11 Quantitative Analysis

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

13 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 13 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?

14 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 14 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

15 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 15 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" MedianMode Central Tendency Average (Mean)

16 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 16 Mean Mean (arithmetic mean) of data values

17 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 17 Mean  The most common measure of central tendency  Affected by extreme values (outliers) 0 1 2 3 4 5 6 7 8 9 100 1 2 3 4 5 6 7 8 9 10 12 14 Mean = 5Mean = 6

18 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 18 Median Median: The “middle” number Not affected by extreme values 0 1 2 3 4 5 6 7 8 9 10 Median = 5 0 1 2 3 4 5 6 7 8 9 10 12 14 Median = 5

19 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 19 Mode Mode: Value that occurs most often  Not affected by extreme values  There may be no mode  There may be several modes Mode = 9 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 0 1 2 3 4 5 6 No Mode

20 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 20 Simple quantitative analysis  Graphical representations give overview of data

21 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 21 Simple quantitative analysis  Graphical representations give overview of data

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

23 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 23 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

24 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 24 Qualitative Analysis

25 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 25 Qualitative Data  Narratives, logs, experience  Interviews  Diaries and journals  Notes from observations  Photographs  Video recordings

26 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 26 What is Qualitative Research?  Research studies that investigate the quality of  Relationships  Activities  Situations  Materials

27 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 27 Qualitative Data Analysis Used for any non-numerical data collected as part of the evaluation  Unstructured observations  Analysis of written documents  Diaries, observations

28 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 28 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?

29 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 29 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

30 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 30 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.

31 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 31 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.

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

33 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 33 Thanks for your attention


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