1. Introduction to research 1703423-2 Analyzing and interpreting research data
Dr Naiema Gaber

2. Analyzing and interpreting research data The learning objectives
After this lecture the student will be able to:
Define data analysis procedures
Describe how to prepare and organize the data for analysis
Explain the coding process of the data
Differentiate the types of Statistics
Determine ways of representing and reporting the findings
Discuss how to interpret the findings
Identify methods of validating the accuracy and credibility of the findings
Describe how to draw conclusions

3. DATA ANALYSIS PROCEDURES
Data analysis is an eclectic process. Occurs simultaneously with data collection, data interpretation and report writing.
Is based on the on data reduction and interpretation
It can be manual or computerized

4. Preparing data for analysis
 scoring: assigning a total to each participant’s instrument
 tabulating: organizing the data in a systematic manner
 coding: assigning numerals (e.g., ID) to data

5. How do You Prepare and Organize the Data?
Develop a matrix to organize the material
Organize material by type
Keep duplicate copies of materials
Transcribe (copy out) data
Prepare data for hand or computer analysis (and select computer program)
Educational Research 2e: Creswell

6. How do you Explore and Code the Data?
Obtain a general sense of the data by performing a preliminary exploratory analysis
Memo ideas
Consider whether more data are needed
Coding the data
Educational Research 2e: Creswell

7. Steps in Coding Read through all transcripts Start with one transcript
Identify text segments – ask “what is this person saying?”
Bracket text segment
Assign code word
Reduce redundancy (unemployment data)
Collapse codes into themes
Educational Research 2e: Creswell

8. A Visual Model of the Coding Process in Qualitative Research
Reduce Codes to
5-7 Themes
Initially read
through data
Divide text
into segments
of information
Label
segments of
information
with codes
Reduce
Overlap and
redundancy
of codes
Collapse
codes into
themes
Many
Pages
of Text
Segments
30-40
codes
Codes
reduced
to 20
Educational Research 2e: Creswell

9. How do You Use Codes to Build Description?
Describe
People
Events
Activities
Processes
Educational Research 2e: Creswell

10. Managing Data Regardless of data type, managing data involves
familiarizing yourself with appropriate software
developing a data management system
systematically organizing and screening data
entering the data into a program
‘cleaning’ your data
do right statistics (descriptive or Inferential)
O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

11. Statistics
It’s important for researchers to be familiar with the language and logic of statistics, and be competent in the use of statistical software.
O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

12. Descriptive Statistics
Descriptive statistics are used to summarize the basic feature of a data set through
measures of central tendency (mean, mode, and median)
dispersion (range, quartiles, variance, and
standard deviation)
distribution (skewness and kurtosis)
O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

13. Inferential Statistics
Inferential statistics allow researchers to assess their ability to draw conclusions that extent beyond the immediate data, e.g.
if a sample represents the population
if there are differences between two or more groups
if there are changes over time
if there is a relationship between two or more variables
O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

14. Selecting Statistical Tests
Selecting the right statistical test relies on
knowing the nature of your variables
their scale of measurement
their distribution shape
types of question you want to ask
O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

15. How to present data
Graphs (frequency polygon, pie chart, boxplot, stem-and-leaf chart)
Measures of central tendency (modem, median, mean
Measures of variability (range, quartile deviation, variance, standard deviation)
Measures of relative position (percentile ranks, standard scores)
Measures of relationship (Spearman Rho, Pearson r

16. How do You Represent Findings?
Comparison table
Descriptive table
Hierarchical tree
Figures/diagrams
Drawings
Educational Research 2e: Creswell

17. How do You Interpret Findings?
Interpretation is not neutral
Reflect about the personal meaning of the data
Compare and contrast personal viewpoints with the literature
Address limitations of the study
Make suggestions for future research
Educational Research 2e: Creswell

18. How do You Validate the Accuracy of Your Findings?
Member checking: Members check the accuracy of the account
Triangulation: Using corroborate evidence
External: Hiring the services of an individual outside the study to review the study
Educational Research 2e: Creswell

19. Drawing Conclusions
Your findings and conclusions need to flow from analysis and show clear relevance to your overall project
Findings should be considered in light of
significance
current research literature
limitations of the study
your questions, aims, objectives, and theory
O'Leary, Z. (2005) RESEARCHING REAL-WORLD PROBLEMS: A Guide to Methods of Inquiry. London: Sage. Chapter 11.

20. Summary of the lecture steps of data analysis include:
Preparing data for analysis by scoring, tabulating and coding.
Managing Data, by choosing the appropriate software, developing a data management system, systematically organizing and screening data, entering the data into a program and the Selecting right statistical test
Interpret Findings
Validate the accuracy of findings
Draw Conclusions
present data

21. Feedback questions
Put T if the statement is true and F if it is false 1- The analysis of the data is as important as any other component of the research process T F 2-Data analysis is an eclectic process based on the on data reduction and interpretation 3- The first step in data analysis is to describe, or summarize, the data using descriptive statistics 4- To test a hypothesis adequately, more than descriptive statistics are normally needed 5- Tabulating: organizing the data in a systematic manner

22. THANK YOU