RS 6003
RESEARCH METHODS AND STATISTICAL ANALYSIS

Written Exam (30%)


Read the following instructions carefully before preparing for your exam

You are required to write an exam at the end of the course that will test your knowledge and
understanding of quantitative and qualitative methodology as well as statistics. Once you have
completed the course, you should be able to:

a. Describe the various study designs and their pros and cons.
b. Explain the principles involved in measurement and instrumentation.
c. Describe the methodology and analytical procedures involved in qualitative research.
d. Select appropriate statistical methods to analyze data and interpret research findings,
including the use of software packages (SPSS).

Please refer to the evaluation form on the next page for details.


Written Exam – Rubrics (30%)


Criteria Excellent
(more than 80%)
Good
(60 – 79%)
Satisfactory
(40 – 50%)
Unsatisfactory
(20 – 39%)
Very unsatisfactory
(less than 20%)
Score

Knowledge and
understanding
of quantitative
study designs
and principles of
measurements


Describes the pros
and cons of
quantitative study
designs, is able to
apply them
correctly and
explain the choices,
principles of
measurements
clearly identified
and articulated;
demonstrates a high
level of
applicability of all
quantitative
research concepts


Describes the pros
and cons of multiple
quantitative study
designs and is able
to apply them
correctly most of the
time, principles of
measurements are
identified but not
completely
articulated;
demonstrates a good
level of applicability
of quantitative
research concepts
most of the time


Describes the pros and
cons of multiple
quantitative study
designs, some
measurements
principles are not
clearly articulated or
are incomplete;
demonstrates
applicability of
quantitative research
concepts some of the
time


Demonstrates a fair
understanding of
quantitative study
designs, and limited
knowledge of
principles of
measurements, show
limited level of
applicability of
quantitative research
concepts most of the
time


Does not
demonstrate
sufficient knowledge
of quantitative study
designs, principles
of measurements
principles and
related research
concepts





/10

Criteria Excellent
(more than 80%)
Good
(60 – 79%)
Satisfactory
(40 – 50%)
Unsatisfactory
(20 – 39%)
Very unsatisfactory
(less than 20%)
Score

Knowledge and
understanding
of paradigms,
qualitative
methodology,
method and data
analysis


Ontology and
epistemology are
correctly identified,
demonstrates a
sophisticated
understanding of
qualitative
methodology, uses
a correct
vocabulary for
qualitative methods
and data analysis
procedures and is
able to apply them
critically

Research concepts
(e.g. ontology,
epistemology..) are
clearly articulated
most of the time,
demonstrates a good
level of
understanding of
qualitative
methodology by
using appropriate
vocabulary most of
the time, is able to
present methods and
data analysis
procedures clearly


Some research
concepts (e.g.
ontology,
epistemology..) are not
sufficiently clear;
demonstrates a certain
level of understanding
of most qualitative
methodology by using
appropriate
vocabulary some of
the time, methods and
data analysis
procedures are
correctly identified
most of the time

There is some
confusion regarding
concepts of
qualitative research
methods (e.g.
ontology,
epistemology..), some
of the vocabulary
regarding qualitative
methodology,
methods and data
analysis procedures is
confusing

Qualitative research
methodology and its
related concepts
(e.g. ontology,
epistemology, …)
are not mastered and
there are major
errors in presenting
qualitative
methodology,
methods and data
analysis procedures




/10

Knowledge and
understanding
of statistical
concepts

Choices of
statistical methods
to analyze data and
interpret research
findings are almost
always correct;
interpretation of
data tables is
mostly error-free
Choices of
statistical methods
to analyze data and
interpret research
findings are largely
correct with
occasional errors;
some minor errors
in the interpretation
of data tables
Choices of statistical
methods to analyze
data and interpret
research findings are
correct most of the
time; interpretation of
data tables are correct
most of the time

Choices of statistical
methods to analyze
data and interpret
research findings are
correct occasionally;
significant errors in
the interpretation of
data tables
Choices of
statistical methods
to analyze data and
interpret research
findings are
incorrect most of
the time; major
errors in the
interpretation of
data tables.