Tools of Research
Week 2 Lecture 1
Thursday, Mar. 18th,
2004
1
Agenda
•
•
•
•
•
The library and its resources
Internet
Techniques of measurement
Statistics
The human mind
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
2
The Library and Its Resources
• Electronic Journals
• Week 3, lecture 1 will have detailed
introduction on how to use the USYD
library system
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
3
Internet
• Finding literature
• Collecting data
– Download secondary data
• Web crawler
– Collect primary data
• Online experiment
• Online survey
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Measurement -- Definition
• Definition
– Measurement is limiting the data of any
phenomenon – substantial or
insubstantial – so those data may be
interpreted and, ultimately, compared to
an acceptable qualitative or quantitative
standard.
– Substantial measurement
• Execution time, throughput, and so on..
– Insubstantial measurement
• User-friendliness, Attitudes, feelings, opinions
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Measuring insubstantial phenomena
• The scenario
– A group of 9 people, who work together in a
personnel department of a large
corporation, are going to attend a
recognition dinner at an exclusive hotel.
After arriving, they greet each other and
have a brief conversation before dinner.
They form some conversation groups as
show in next slides
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Interpersonal relationships
• How to measure the interpersonal dynamics of the
group?
– Who greet whom with enthusiasm or with indifference?
– Who joins in conversation with whom?
– Who seems to be a relative outsider?
• To merely observe the behavior of individuals in a
particular situation is not to measure it.
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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A possible approach
• Ask each person in the group to record
three choices
– The individual in the group whom the
person likes most
– The individual in the group whom the
person like least
– The individual for whom the person has no
strong feeling one way or another.
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Sociogram
• Weight the data
into numerical
categories
– +1 for a
positive choice
– 0 for
indifference
– -1 for a
negative
choice
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Sociometric matrix
Gretchen
Joe
Greg
Sara
Peter
Jeff
Tim
Matt
Terri
Gretchen
---
0
0
0
-1
+1
0
+1
0
Joe
0
---
0
0
+1
+1
0
0
0
Greg
0
0
---
0
0
+1
0
+1
0
Sara
0
0
0
---
+1
0
0
0
+1
Peter
0
+1
0
0
--
-1
0
0
+1
Jeff
+1
+1
0
0
0
---
0
0
0
Tim
0
0
+1
0
-1
+1
---
0
0
Matt
+1
0
0
0
0
+1
0
---
0
Terri
0
0
0
+1
+1
0
0
0
---
Totals
2
2
1
1
1
4
0
2
3
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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What we can discover?
• Jeff is the in formal or popular leader
• Probably some schism and tension are
present in this group
• Friendship pairs may lend cohesion to
the group
• Tim apparently is the isolate of the group
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Four scales of measurement
• Nominal scale of measurement
– Measure data to some degree by assigning
names (numbers) to them.
– Elemental and unrefined,
– typical use: classification
• Male-female
• Social classes
– Only a few statistics are appropriate for
analyzing nominal data
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Four scales of measurement
• Ordinal scales of measurement
– Data can be rank-ordered
• Level of education: elementary, high school,
college and graduate education.
– Distance between attributes do not have
any meaning
– Typical use – rankings
• Preference data
• Attitude measures
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Four scales of measurement
• Interval scale of measurement
– Features
• It has equal units of measurement
• Its zero point has been established arbitrarily
– Typical use:
• Temperature scales: Fahrenheit and Celsius
• Rating scales employed by many businesses, survey
groups and professional organizations are often assumed
to be on interval scales
1. How would you rate the availability of your professor for conferences?
0
1
2
3
4
Never
available
Seldom
available
Available by
appointment
only
Generally
available
Always
available
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Four scales of measurement
• Ratio scale of measurement
– Difference between interval and ratio scales
• Temperature: We can’t say 30C is twice as warm as 15C.
• Execution time: 30 seconds is twice as fast as 15
seconds
– Features
• It has equal units of measurement
• It has an absolute zero point
– It is possible to multiply and divide scale numbers
meaningfully and thereby form ratios
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Measurement Scales: summary
• If you can say that
– One object is different from another, you have a
nominal scale;
– One object is bigger or better or more of anything
than another, you have an ordinal scale;
– One object is so many units(degrees, inches) more
than another, you have an Interval scale;
– One object is so many times as big or bright or tall
or heavy as another, you have a ratio scale.
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Mini workshop
• Indicate the levels of measurements of
the following variables:
VARIABLES
HOW VARIABLES MEASURED
Attendance
How often do you attend religious services?
(0) Never, (1) less than once a year, (2) several times a
year, … (8) several times a week?
IQ Score
Most intelligence tests are organized with 100 as
average, middle, or normal. Scores higher or lower
indicate distance from the average
Religion
Could be Jewish, catholic, Lutheran, Baptist
Age
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Validity and reliability of measurement
• Validity
– The extent to which the instrument
measures what it is supposed to measure
• Well-established measurement
• Other measurement, measurement of
insubstantial phenomena
– To what extent does a standardized IQ test actually
measure a person’s intelligence?
– Problem of “Professor’s availability” measurement
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Validity and Reliability of measurement
• Reliability
– The stability and consistency of a measure
• Validity vs. Reliability
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Statistics as a tool of research
• Primary functions of statistics
– Descriptive
• Summarize the general nature of the data obtained
–
–
–
–
What’s the average
How disperse the data are
How closely two or more characteristics are Interrelated
more
– Inferential
• Help the researcher make decisions about the data
– Statistics software
• Excel
• SPSS, SAS
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
20
The human mind as a tool of research
• Methods of knowing
– Method of tenacity
– Method of authority
– Method of intuition (a priori method)
– Method of Science
• Self-correction
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
21
The human mind as a tool of research
• Deductive Logic
– Starts from one or more premises, draw conclusion
through logic reasoning
• Premise: All tulips are plants
• Premise: All plants produce energy through
photosynthesis
• Conclusion: All tulips must produce energy through
photosynthesis
– Premise can be false
• Premise: All metals expand when heated
• Premise: Tulips are metals
• Conclusion: Tulips will expend when heated
– Deductive logic is extremely valuable for
generating research hypotheses and testing them
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
22
The human mind as a tool of research
• Inductive Reasoning
– Begins with empirical observations and
draw general conclusions from them
• Observations: Psychiatrists have found that
psychological problems in patients depend upon
their experiences in childhood
• Conclusion: All psychological problems are
based on experiences in childhood.
– We can never be 100 percent sure about
the inductive conclusions
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
23
Induction and Deduction
Laws and theories
induction
Facts acquired
through observation
Thursday, Mar. 18th, 2004
deduction
Explanations and
Predictions
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Scientific Method
• Control
– Enable researcher to identify the causes of his or her
observation
• Operational definition
– Terms must be defined by the steps or operations used to
measure them
• “Anxiety causes students to score poorly in test”
• What is meant by “anxiety”?
• Replication
– The same result must be found if the study is repeated
• Hypothesis testing
– “being ill is a punishment for being sinful”
– “Boys are better than girls at mathematics”
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Critical thinking
•
•
•
•
Verbal reasoning
Argument analysis
Decision making
Critical analysis of prior research
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Facility with language
• Communicating effectively through writing
– Say what you mean to say
– Keep your primary objective in writing your paper
in mind at all times, and focus your discussion
accordingly
– Provide an overview of what you will be talking
about
– Organize your ideas into general and more specific
categories and use headings and subheadings to
guide your readers through your discussion of
these categories
– Provide transitional phrases
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Facility with language
– Use concrete examples to make abstract
ideas more understandable
– Use appropriate punctuation
– Use figures and tables when such
mechanisms can more effectively present
or organize your ideas and findings
– At the conclusion of a chapter or major
section, summarize what you’ve said
– Anticipate that you will almost certainly
have to write multiple drafts.
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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Summary
• The library and its resources
• Internet
• Techniques of measurement
– How to measure intangible concept
– Different scales of measurements
– Validity and reliability
• Statistics
– Descriptive and inferential
– Several statistics packages
• The human mind
Thursday, Mar. 18th, 2004
ISYS3015 Analytical Methods for IS Professionals
School of IT, The University of Sydney
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