©2011 1www.id-book.com Data analysis, interpretation and presentation Chapter 8.

Slides:



Advertisements
Similar presentations
Web Page Design Critical Elements for a Well Designed Web Page.
Advertisements

Grounded Theory   Charmaz (2008).
Chapter 8 Data Analysis, Interpretation and Presentation.
© Done by : Latifa Ebrahim Al Doy Chapter 8 Data analysis, interpretation and presentation and presentation.
Data analysis and interpretation. Agenda Part 2 comments – Average score: 87 Part 3: due in 2 weeks Data analysis.
Kazuya Sakai Graduate Student Dept. of CSSE, Auburn University Ch 8.6 Using Theoretical Framework.
Statistics for Decision Making Descriptive Statistics QM Fall 2003 Instructor: John Seydel, Ph.D.
Observing users.
Observing users. The aims Discuss the benefits & challenges of different types of observation. Describe how to observe as an on-looker, a participant,
SOWK 6003 Social Work Research Week 10 Quantitative Data Analysis
Observing Behavior A nonexperimental approach. QUANTITATIVE AND QUALITATIVE APPROACHES Quantitative Focuses on specific behaviors that can be easily quantified.
Chapter 9 Principles of Analysis and Interpretation.
Data Analysis, Interpretation, and Reporting
CHAPTER 13, qualitative data analysis
Evaluating and Presenting Collected Data Class 33.
Descriptive Statistics Used to describe the basic features of the data in any quantitative study. Both graphical displays and descriptive summary statistics.
Research Terminology for The Social Sciences.  Data is a collection of observations  Observations have associated attributes  These attributes are.
FOCUS GROUPS ANALYSIS OF QUALITATIVE DATA
Qualitative Analysis A qualitative researcher starts with a research question and little else! Theory develops during the data collection process. Theory.
Research Methods in Computer Science Lecture: Quantitative and Qualitative Data Analysis | Department of Science | Interactive Graphics System.
Data analysis, interpretation and presentation
1 Research Paper Writing Mavis Shang 97 年度第二學期 Section VII.
Chapter Two: Summarizing and Graphing Data 2.2: Frequency Distributions 2.3: ** Histograms **
Computer Science Department California Polytechnic State University San Luis Obispo, CA, U.S.A. Franz J. Kurfess CPE/CSC 484: User-Centered Design and.
CHAPTER III IMPLEMENTATIONANDPROCEDURES.  4-5 pages  Describes in detail how the study was conducted.  For a quantitative project, explain how you.
 Data gathering and analysis  Class activity  Discuss eye tracking assignment.
Market Research Lesson 6. Objectives Outline the five major steps in the market research process Describe how surveys can be used to learn about customer.
Analyzing and Interpreting Quantitative Data
Data analysis, interpretation and presentation (Chapter 8 – Interaction Design Text) The kind of analysis can be performed on the data depends on the goals.
AVI/Psych 358/IE 340: Human Factors Data Analysis October 22-24, 2008.
Data analysis and interpretation. Project part 3 Watch for comments on your evaluation plans Finish your plan – Finalize questions, tasks – Prepare scripts.
PROCESSING OF DATA The collected data in research is processed and analyzed to come to some conclusions or to verify the hypothesis made. Processing of.
PROCESSING, ANALYSIS & INTERPRETATION OF DATA
Making sense of it all analysing and interpreting data.
Data Analysis, Interpretation, and Presentation Devin Spivey Asmae Mesbahi El Aouame Rahul Potghan.
Chapter 2 Doing Sociological Research Key Terms. scientific method Involves several steps in research process, including observation, hypothesis testing,
Cat 2 Non Experimental Research Projects Day Competition 2009.
Analysing qualitative data
Observing users. The aims Discuss the benefits & challenges of different types of observation. Describe how to observe as an on-looker, a participant,
How to Organize Findings, Results, Conclusions, Summary Lynn W Zimmerman, PhD.
Data analysis, interpretation, and presentation
Program Evaluation for Nonprofit Professionals Unit 4: Analysis, Reporting and Use.
Observing users. What and when to observe Goals & questions determine the paradigms and techniques used. Observation is valuable any time during design.
Analysis Perspectives for qualitative data Basing data analysis around theoretical frameworks provides further insight Three such frameworks are: –Grounded.
Evaluation and Assessment of Instructional Design Module #4 Designing Effective Instructional Design Research Tools Part 2: Data-Collection Techniques.
 Two types of analysis based on the data that is generated.  Quantitative or  Qualitative  Basic descriptive statistics such as mean, median, and.
Data Gathering and Analysis
Data Analysis, Interpretation and Presentation
Organizing, Analyzing, & Interpreting Data
Analysis of Data Qualitative Data Analysis
Chapter 6: Observing Behaving
Data Analysis, Interpretation and Presentation
Data analysis, interpretation
Quantitative and qualitative
Information used to create graphs and find statistics
Data analysis and interpretation
Data analysis, interpretation and presentation
THE ANALYTICAL FRAMEWORK
Data analysis, interpretation and presentation
Data Analysis, Interpretation and Presentation
Defining Tasks; Data Analysis
Mean: average 2. Median: middle number 3. Mode: most often
Observing users.
Like all science, biology is a process of inquiry.
Data analysis, interpretation and presentation
Good Morning AP Stat! Day #2
Data analysis, interpretation and presentation
Ass. Prof. Dr. Mogeeb Mosleh
Data Analysis Dr. Sampath Jayarathna Old Dominion University
Data Analysis, Interpretation, and Presentation
Presentation transcript:

©2011 1www.id-book.com Data analysis, interpretation and presentation Chapter 8

©2011 2www.id-book.com Overview Qualitative and quantitative Simple quantitative analysis Simple qualitative analysis Tools to support data analysis Theoretical frameworks: grounded theory, distributed cognition, activity theory Presenting the findings: rigorous notations, stories, summaries

©2011 3www.id-book.com Quantitative and qualitative Quantitative data – expressed as numbers Qualitative data – difficult to measure sensibly as numbers, e.g. count number of words to measure dissatisfaction Quantitative analysis – numerical methods to ascertain size, magnitude, amount Qualitative analysis – expresses the nature of elements and is represented as themes, patterns, stories Be careful how you manipulate data and numbers!

©2011 4www.id-book.com 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 Graphical representations give overview of data

©2011 5www.id-book.com Visualizing log data Interaction profiles of players in online game Log of web page activity

©2011 6www.id-book.com Web analytics

©2011 7www.id-book.com Simple qualitative analysis Recurring patterns or themes –Emergent from data, dependent on observation framework if used Categorizing data –Categorization scheme may be emergent or pre-specified Looking for critical incidents –Helps to focus in on key events

©2011 8www.id-book.com Tools to support data analysis Spreadsheet – simple to use, basic graphs Statistical packages, e.g. SPSS Qualitative data analysis tools –Categorization and theme-based analysis, e.g. N6 –Quantitative analysis of text-based data CAQDAS Networking Project, based at the University of Surrey (

©2011 9www.id-book.com Theoretical frameworks for qualitative analysis Basing data analysis around theoretical frameworks provides further insight Three such frameworks are: –Grounded Theory –Distributed Cognition –Activity Theory

© www.id-book.com Grounded Theory Aims to derive theory from systematic analysis of data Based on categorization approach (called here ‘coding’) Three levels of ‘coding’ –Open: identify categories –Axial: flesh out and link to subcategories –Selective: form theoretical scheme Researchers are encouraged to draw on own theoretical backgrounds to inform analysis

© www.id-book.com Distributed Cognition The people, environment & artefacts are regarded as one cognitive system Used for analyzing collaborative work Focuses on information propagation & transformation

© www.id-book.com Activity Theory Explains human behavior in terms of our practical activity with the world Provides a framework that focuses analysis around the concept of an ‘activity’ and helps to identify tensions between the different elements of the system Two key models: one outlines what constitutes an ‘activity’; one models the mediating role of artifacts

© www.id-book.com Individual model

© www.id-book.com Engeström’s (1999) activity system model

© www.id-book.com Presenting the findings Only make claims that your data can support The best way to present your findings depends on the audience, the purpose, and the data gathering and analysis undertaken Graphical representations (as discussed above) may be appropriate for presentation Other techniques are: –Rigorous notations, e.g. UML –Using stories, e.g. to create scenarios –Summarizing the findings

© www.id-book.com Summary The data analysis that can be done depends on the data gathering that was done Qualitative and quantitative data may be gathered from any of the three main data gathering approaches Percentages and averages are commonly used in Interaction Design Mean, median and mode are different kinds of ‘average’ and can have very different answers for the same set of data Grounded Theory, Distributed Cognition and Activity Theory are theoretical frameworks to support data analysis Presentation of the findings should not overstate the evidence