1. The Research Process OBSERVATION Broad Area of Research Interest
PROBLEM DEFINITION
Research problem delineated
THEORETICAL FRAMEWORK
Variables clearly identified
GENERATION OF HYPOTHESES
PRELIMINARY DATA GATHERING
Interviews & Literature review
DEDUCTION
Hypotheses substantiated? Research Questions answered?
DATA COLLECTION, ANALYSIS & INTERPRETATION
Muhamad Jantan:
Introduction to Data Analysis

2. Introduction to Data Analysis
Data Analysis - Issues
What is data analysis?
Types of techniques
Identifying the right technique
Using computers to analyse data
Reporting the analysis
Muhamad Jantan:
Introduction to Data Analysis

3. The Data Analysis Process
Questionnaire Editing
Generating Composite Measures
Editing the SPSS Output
Transfer Edited SPSS output to Word File
Data Entry & Data Definition
Data Validation
Testing Goodness of Measure
Identifying the Right Technique
Syntax Command to SPSS
Interpreting the SPSS Output
Report Writing
In most cases, the process is not sequential and linear, but more iterative where you may need to go back to some steps to explore further
Muhamad Jantan:
Introduction to Data Analysis

4. Introduction to Data Analysis
Data Analysis - Types
Purpose of Study
Exploratory; Test of Differences; Establishing Relationships
Number of Variables
Univariate; Bivariate; Multivariate
Level of Measurements
Nominal, Ordinal, Interval & Ratio
Muhamad Jantan:
Introduction to Data Analysis

5. Purpose of Study - Exploratory
Basically to address the issue of “What is the current situation – vis-à-vis the phenomenon of interest?”
Example:
What is the current level of innovation of Malaysian Companies?
What is the preferences of Malaysian consumers of organic food?
What percentage of the Malaysian consumers will use internet banking?
Etc…..
Muhamad Jantan:
Introduction to Data Analysis

6. Purpose of Study – Test of Differences
To address the question of “Is there a difference between Type A and Type B in terms the phenomenon of interest, Y?”
Example:
Are companies in the electronics sector more innovative than companies in the food sector?
Are consumers in the professional line more likely to use internet banking compared to those in other occupation?
Is the preference for organic food higher for urban consumers compared to consumers living in the rural areas?
Muhamad Jantan:
Introduction to Data Analysis

7. Purpose of Study – Establishing Relationships
To address the question of “Is there a relationship between phenomenon X with phenomenon, Y?”
Example:
The larger the company, the more innovative it is?
The more business a company undertakes the more likely is the company to use internet banking?
The more the consumer believe that organic food is good for the health, the more likely he/she is to consume organic food.
The more secure is internet banking, the more user-friendly is the system, and the easier to access the system, the more likely a company is to use internet banking.
Muhamad Jantan:
Introduction to Data Analysis

8. Number of Variables - Univariate
Analysis involves only one variable
Exploratory studies typically involve univariate analysis
Example:
What is the current level of innovation of Malaysian Companies?
What is the preferences of Malaysian consumers of organic food?
What percentage of the Malaysian consumers will use internet banking?
Muhamad Jantan:
Introduction to Data Analysis

9. Number of Variables - Bivariate
Analysis involves two variables
Test of differences involves two variables
Establishing relationships may involve bivariate analysis (correlation)
Example:
Are companies in the electronics sector more innovative than companies in the food sector? – sector & level of innovation
The more business a company undertakes the more likely is the company to use internet banking? – size (in terms of business transactions) & likelihood of using internet banking
Muhamad Jantan:
Introduction to Data Analysis

10. Number of Variables - Multivariate
Analysis involves three or more variables
Analysis typical when trying to establish relationships
Example:
The more secure is internet banking, the more user-friendly is the system, and the easier to access the system, the more likely a company is to use internet banking. – security, user-friendliness, ease of access, and likelihood of using internet banking
Muhamad Jantan:
Introduction to Data Analysis

11. Data Types – Levels of Measurement
Purpose of Study
Exploratory; Test of Differences; Establishing Relationships
Number of Variables
Univariate; Bivariate; Multivariate
Level of Measurements
Nominal, Ordinal, Interval & Ratio
Muhamad Jantan:
Introduction to Data Analysis

12. Data Types - Levels of Measurements
Muhamad Jantan:
Introduction to Data Analysis

13. Introduction to Data Analysis
Nominal Scale
Classificatory or Categorical
e.g. Sex – Male/Female
Colour
Mutually exclusive & collectively exhaustive
Muhamad Jantan:
Introduction to Data Analysis

14. Introduction to Data Analysis
Ordinal Scale
Categorize and rank
e.g. Preference in job attributes
Please rank from 1 most important to 5 least important the following attributes:
Interacting with others
Using multiple skills
Completing a task from beginning to end
Serving others
Work independently
Muhamad Jantan:
Introduction to Data Analysis

15. Introduction to Data Analysis
Interval Scale
Allows for measurement of distance between two points on the scale
e.g. Preference in job attributes
Using a scale of 1 (strongly disagree), 2 (disagree), 3 (neither agree nor disagree), 4 (agree) and 5 (strongly agree), please indicate the extent of your agreement by circling the appropriate number.
The following are very important to me
Interacting with others 1 2 3 4 5
Using multiple skills
Complete a task from beginning to end
Serving others
Working independently
Muhamad Jantan:
Introduction to Data Analysis

16. Introduction to Data Analysis
Ratio Scale
Has absolute zero; thus allowing for not only differences but also proportions in the differences
e.g. Number of years in the organization
Muhamad Jantan:
Introduction to Data Analysis

17. Introduction to Data Analysis
The Right Technique?
Research Question
Concern for Central Tendency;
Comparing groups; Relationships
Number of Variables
Univariate; Bivariate; Multivariate
Level of Measurements
Parametric and Non-parametric
Muhamad Jantan:
Introduction to Data Analysis

18. The Right Technique? What is the purpose of the analysis?
What is the level of measurement?
How many variables are involved?
Muhamad Jantan:
Introduction to Data Analysis

19. Introduction to Data Analysis
Descriptive Analysis
Purpose:
To describe the distribution of the variables of interest
Answers the question of “What is ...?”
Techniques
Frequencies Distribution - if 1 ordinal or nominal variable,
Cross-tabulation - if 2 ordinal or nominal variables
Means - if 1 interval or ratio level variable
Means of subgroups - if 1 interval or ratio level variable by subgroups
Muhamad Jantan:
Introduction to Data Analysis

20. Introduction to Data Analysis
Test of Differences
Purpose:
To evaluate the differences between 2 or more groups with respect to a variable of interest
Techniques depends on
Levels of Measurement of the Variable
Number of Groups
Independence of the Groups
Muhamad Jantan:
Introduction to Data Analysis

21. Test of Differences More than 2 group? Yes Are they independent?No
Yes
Are they independent?
Are they independent?
Nominal: 2 - test
Ordinal: Friedman 2-way ANOVA
Continuous: Factorial 2-way ANOVA
Yes
Yes No No
Nominal: 2-test
Ordinal: Mann-Whitney
Continuous: t-test
Nominal- McNemar
Ordinal - Wilcoxon Signed Rank
Continuous: Paired t-test
Nominal: 2 test
Ordinal: Kruskal-Wallis ANOVA
Continuous: 1-way ANOVA
Muhamad Jantan:
Introduction to Data Analysis

22. Introduction to Data Analysis
Relationship
Purpose:
To establish relationship between variables
Techniques depends on
Whether or not there exist dependent variable(s)
Number of dependent and independent variables
Levels of Measurement of the Variable
Muhamad Jantan:
Introduction to Data Analysis

23. Dependence Relationships
How many dependent variables?
More than 1
One
Scale of Dependent
Scale of Dependent
Nominal
Scale of Independent
Interval
Interval
Scale of independent
Scale of Independent
Scale of Independent
Conjoint Analysis
Nominal
Interval
Interval
Nominal
Interval
Nominal
Multiple Regression
ANOVA
Discriminant Analysis
Canonical Correlation
Multivariate ANOVA
Muhamad Jantan:
Introduction to Data Analysis