Research Methods in Computer Science Lecture: Quantitative and Qualitative Data Analysis 22.04.2017 | Department of Science | Interactive Graphics System (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Data Analysis Sorted data Student No Hours Studied Marks 1 40 2 4 80 3 50 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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Quantitative Analysis University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 10 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Mean Mean (arithmetic mean) of data values University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 15 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Mean 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 = 6 Mean = 5 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 16 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 17 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 Mode = 9 No Mode University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 18 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Simple quantitative analysis Graphical representations give overview of data University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 19 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Simple quantitative analysis Graphical representations give overview of data University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 20 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

Qualitative Analysis University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 23 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner

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

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

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

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

Thanks for your attention University Of Malakand | Department of Computer Science | UoMIPS | Dr. Engr. Sami ur Rahman | 36 22.04.2017 | Department of Computer Science | Interactive Graphics Systems Group (GRIS) | Prof. Dr. techn. Dieter Fellner