DATA ANALYSIS FOR CLASS
FIELD WORK
ADESANYA GBENGA
OCTOBER, 2015
OUTLINE OF THE STUDY
 Introduction
 Sources of data
 Basic steps in qualitative data analysis
 Methods of qualitative data analysis
 Basic steps in quantitative analysis
 Methods of quantitative data analysis
 Facts about data analysis
 Conclusion
INTRODUCTION
 Data: is information that has been translated into a form that is more convenient to move
or process. Data are facts and statistics collected together for reference or analysis.
 Data Analysis: is the process of systematically applying statistical and/or logical techniques
to describe and illustrate, condense and recap and evaluate data
 Quantitative Data Analysis:
 It is a systematic approach to investigations during which numerical data is collected.
 The researcher transforms what is collected or observed into numerical data.
 It involves measuring or counting attributes.
INTRODUCTION (Cont.)
Qualitative Data Analysis?
• It is the range of processes and procedures whereby a researcher transforms
qualitative data that have been collected into some form of explanation,
understanding .
• It is the interpretation of the people and situations a researcher is
investigating.
• It is usually based on an interpretative philosophy
Report and
Evaluate
Research
Analyse and
Interpret Data
Identify the
Research
Problem
Collect Data
Review the
Literature
Specify a
Research
Purpose
The Process of
Research
The Process of
Research
The Process of Research
RESEARCH DATA
Primary
Data
Research
Data
Secondary
Data
SOURCES OF DATA
Research
Data
Secondary
Data
Primary Data
Quantitative
Survey
Observation
Cellphone
Experimental
Focus Group
Questionnaire
Face-to-Face
Qualitative
Mail
Internet
Personal
Interview
Interviews
Project
Techniques
Telephone
Interview
BASIC STEPS IN QUALITATIVE DATA
ANALYSIS
Documentation of the data and the process of data collection.
Organization or categorization of the data into concepts.
Connection of the data to show how one concept may influence another.
Corroboration/legitimization, by evaluating alternative explanations,
disconfirming evidence and searching for negative cases
Representing the account i.e. reporting the findings
METHODS OF QUALITATIVE DATA
ANALYSIS
Typology - a classification system, taken from patterns, themes, or
other kinds of groups of data.
Constant Comparison/Grounded Theory – it involves
• Looking at documents such as field notes
• Looking for indicators of categories in events and behavior - name
them and code them on document
• Compare codes to find consistencies and differences
METHODS OF QUALITATIVE DATA
ANALYSIS (Cont.)
Discourse analysis: You use tapes so they can be played and replayed. It
involves the discussion of several people, not individual person specifically.
Find patterns of questions and other patterns of interaction.
Analytic Induction – it involves looking at an event and developing a
hypothetical statement of what happened i.e. the development of a new
hypothesis. Then look at another similar event and see if it fits the
hypothesis. If it doesn't, revise hypothesis.
Analytic Deduction: It is aimed at testing existing theories. It usually begins
with a hypothesis. It is mostly used in quantitative analysis
THE PROCESS OF INDUCTIVE AND
DEDUCTIVE METHOD IN DATA ANALYSIS
Deductive Analytical Model:
Theory
Hypothesis
 It works from the more general to the more specific.
Observation
 It is informally called a “Top – down approach”
Confirmation
THE PROCESS OF INDUCTIVE AND
DEDUCTIVE METHOD IN DATA ANALYSIS
(Contd)
Inductive Analytical Model:
Theory
Tentative
Hypothesis
Pattern
Observation
BASIC STEPS IN QUANTITATIVE
DATA ANALYSIS
Formulation of an hypothesis: An hypothesis is a statement
about an expected relationship between two or more variables
that permits empirical testing
Selection of variables
Determining the Study Sample Size
Collection of Data
BASIC STEPS IN QUANTITATIVE
DATA ANALYSIS
Preparation of Data: It entails coding, cleaning and organising data
for analysis
Sample Description: It entails describing the sample in terms of
average and variation
Exploration of Models Built on Relevant Variables: It is mostly
done through correlation and regression analysis
Presentation of Data and Findings
Discussion with Relevant Stakeholders
METHODS OF QUANTITATIVE DATA
ANALYSIS
Descriptive Statistics: measures of central tendency
Correlation Technique
Regression Technique
Analysis of Variance (ANOVA)
Other Econometrics Techniques
FACTS ABOUT DATA ANALYSIS
 Acquisition of necessary skills to analyse.
Ability to Draw Unbiased Inference.
Following acceptable norms for disciplines or fields of study.
Basic knowledge of Statistics or Econometrics.
The use of software.
CONCLUSION
Analysing data comes with experience. The more you analyse data, the better
you become.
FOR LISTENING