1. THE ANALYSIS OF EMPERICAL AND QUALITATIVE DATA
Please be welcome!!

2. THE ANALYSIS OF EMPERICAL AND QUALITATIVE DATA
PAPER TITLE
THE ANALYSIS OF EMPERICAL AND QUALITATIVE DATA
 By
 C. Njerekai-Department of Tourism and Hospitality Management, Midlands State University, Gweru, Zimbabwe

3. 1. Why Data Analysis? Decipher meaning
Address research questions and objectives
Make predictions
Make recommendations with respect to the research problem

4. 2. Steps For Data Analysis
Step 1: Edit the data
Why edit the data?
When should editing be done?
In editing data, you could come across the following scenarios. What would you do in each of these?

5. Cont. Inconsistent responses Missing responses/information
Unclear responses
Too consistent responses

6. Step 2: Code the data
Def:Coding refers the process of assigning numerical values to all response categories in questions.
e.g What is your marital status?
single
On separation

7. Coding Cont.
Coding is necessary for the transfer of data into the computer for CAQDAS
There are basically two types of coding
Pre-coding
Post-coding

8. Coding Cont.
The process of coding requires establishment of categories. These categories should be;
Mutually exclusive
Convenient in number
Exhaustive viz; include possible responses like don’t know, not applicable, other etc.

9. Step 3: Analyse the qualitative data
Step 3.1: Transcribe or capture the data
Involves transferring into a manual or computer readable format.
Done for both quantitative and qualitative data

10. Cont.
NB* You should familiarise yourself with the various software packages you will want to use to capture the data.

11. Cont.
Step 3.2: Analyse the qualitative data
The qualitative data analysis techniques that can be used to decipher meaning and draw conclusions from qualitative data are as follows;

12. Qualitative data analysis techniques
Computer assisted qualitative data analysis software. Examples of CAQDAS?
Use of quasi-statistics
Use of topical question list or hermeneutics
Semiotics?

13. Cont.
Taxonomy?
Micro-analysis?
Comparative analysis?
Reconnaissance?

14. Cont. Clutter reduction?
Use of mind maps, flow charts and diagrams to visualize the data
Hunt for connections and develop theory from the data. (Grounded theory)

15. Step 4: Analyse the quantitative data
Step 4.1: Transcribe or capture the data
Discussed
Step 4.2: Undertake Preliminary data analysis
It is advisable to start with simple analysis of data before subjecting it to more complex and sophisticated data analysis.

16. Quantitative data analysis cont.
The preliminary data analysis that can be employed in this endeavour are as follows;
Simple one-way tabulation
Cross-tabulation of data (illustrate)
Statistical summarization of data (See handout 1: Table 2)

17. cont. Step 4.3: Undertake more complex analysis of the data
Achieved through subjecting the data to statistical data analysis techniques. Such statistical data analysis techniques are undertaken to help you make intelligent decisions and conclusions pertaining to the research problem.

18. cont
Measures of association and inferential statistics are the main techniques used in this endeavor. These will be discussed in more detail next;

19. Cont. Measures of association
They relate to the relationship between two or more sets of data. This relationship is most vividly shown through the use of scatter graphs, which clearly bring out the nature and pattern of association.

20. Cont.
ii) Inferential statistics Inferential statistics are used to draw inferences, informal guesses or conclusions on whether certain situations are by chance or are reflective of the true situation.

21. Cont.
However the decision on the statistical tests you will use is taken at the start of the data collection process.
This is because; certain statistical tests only work with certain data collection techniques and the resultant types of data collected e.g. nominal, ordinal, interval data e.t.c.

22. Cont.
The sample size and the population from which you collect the sample can also influence the type of statistical tests to be used. At this point, we would like to reiterate that, a detailed outline of how the various statistical values are computed will not be given in this presentation.

23. Cont.
Rather, situations and examples where these statistical tests can be carried out are shown in table 3. (handout 2: Table 3). You are therefore advised to visit the numerous textbooks on statistics and research methods for a step-by-step derivation of these statistical values.

24. Cont.
Iii) Computer assisted data analysis In this case, the computer makes intelligent decisions and conclusions pertaining to the research problem using measures of association and inferential statistics.

25. Cont.
NB* Outsourcjng of this service is a dis-service to yourself.

26. THE END!!
Thank You!!!