Quantitative vs. Qualitative
v
Qualitative approach:
§
It includes historical research and qualitative
research;
§
It collects narrative data to gain insights into
phenomena of interest;
§
Data analysis includes the coding of the data and
production of a verbal synthesis.
v
Quantitative approach:
§
It is categorized with descriptive research,
correlational research, causal-comparative research and experimental research;
§
It collects numerical data in order to explain, predict
and or control phenomena of interest;
§
Data analysis is mainly statistical.
Types of Quantitative
Researches
v Descriptive: Descriptive research involves collecting
data in order to test hypotheses or answer questions concerning the current
status of the subjects of the study. It
determines and reports the way things are.
v Correlational:
Correlational research attempts to determine whether and to what degree a
relationship exists between two or more quantifiable variables. However, it never establishes a cause-effect
relationship. The relationship is
expressed by correlation coefficient, which is a number between .00 and 1.00.
v Cause-comparative:
Causal-comparative research: establishes the cause-effect relationship, compares
the relationship, but the cause is not manipulated, such as "gender."
v Experimental: Experimental research establishes the
cause-effect relationship and does the comparison, but the cause is
manipulated. The cause, independent
variable makes the difference. The
effect, dependent variable is dependent on the independent variable.
Before Conducting a
Quantitative Research
v
Research
plan: Research plan must be completed before a study is
begun. Why?
§
The plan makes a research to think;
§
A written plan facilitates evaluation of the proposed
study;
§
The plan provides a guide for conducting the study.
Ø Components
of a Research Plan :
§
Introduction:
It includes a statement of the problem, a review of related literature,
and a statement of the hypothesis.
§
Method: This
part includes subjects, instruments-- materials if appropriate, design
procedure.
§
Data analysis: A description of the statistical
technique or techniques that will be sued to analyze study data.
§
Time schedule: The time schedule is equally important
for both beginning researchers working on the thesis or dissertation and for
experienced researchers working under the deadlines of a research grant or
contract. It basically includes a
listing of major activities or phases of the proposed study and a corresponding
expected completion time for each activity.
§
Budget: It should list all tentative expenses
specifically and submitted to funding agency.
It includes such items as personnel, clerical assistance, travel and
postage and other expenses, equipment, and fringe benefits etc.
v
Ethical consideration:
Ø
THREE ethical considerations are:
§
The subjects should not be harmed in any way
(physically or mentally) in the name of science. If an experiment involves any risk to subjects, they should be
completely informed concerning the nature of the risk and the permission for
participation in the experiment should be acquired in writing from the subjects
themselves, or from persons legally responsible for the subjects if they are
not of age. If school children are
involved, it is a good idea to inform parents before the study is conducted if
possible.
§
Subject’s privacy should be strictly confidential. Individual scores should never be reported,
or made public.
§
Ethical principle in the conduct of research with human
participants is the most definitive source of ethical guidelines for
researcher. It is prepared and
published by the American Psychological Association (APA). “.... with respect and concern for the
dignity and welfare of the people who participate and with cognizance of
federal and state regulations and professional standards governing the conduct
of research with human participants.”
That is “to respect and concern for the dignity and welfare of the
people who participate.”
Basic
Concepts of Quantitative Research
a.
Introduction
i.
Defining a problem
ii.
Literature review
iii.
Hypotheses
b.
Method
i.
Population and subjects
ii.
Instruments
iii.
Design and procedures
c.
Results
i.
Data and statistics
1.
Types of measurement scales
2.
Descriptive statistics
a.
Types of descriptive statistics
b.
Calculation for interval data
ii.
Inferential statistics
1.
Level of significance
2.
Tests of significance
a.
t test for independent variables
b.
t test for dependent variables
c.
ANOVA
d.
Discussion
i.
Interpretation of results
ii.
Generalization
iii.
Discussion of implications
e.
Conclusion and recommendation
i.
Based on practical significance to draw conclusion and make
suggestions.
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