Research Design and
Implementation - 2
Data Collection Methods
Table 4-2
Relationship between Data Collection Method and
Category of Research
Category of Research
Data Collection Method
Exploratory
Descriptive
Causal
Secondary Sources
Information System
a
b
Databanks of other
a
b
organizations
Syndicated Services
a
b
b
Primary Sources
Qualitative Research
Surveys
Experiments
a
b
b
a
b
b
a
Research Tactics
 Measurement – Generally what questions do we
ask so that we get the information we want
 Sampling Plan – How do we select a sample for
the study such that we maximize its chances of
faithfully representing the population of interest
 Analysis – confirming that all information being
obtained is appropriate and adequate for
addressing the RQ / hypothesis
Errors in Research Design
 Assume you are interested in knowing what
Winthrop undergrad students feel about the
quality of the faculty
– What is the population? Size?
 Assume you take a sample of 100 students
and find the sample mean
– Would your sample mean match the population
mean?
– If not, what is the difference?
Errors in Research Design
 Assume you get a mean figure of 4.0 on a 1
(low quality) to 5 (high quality) scale
 The population mean is an unknown figure
– Always wise to acknowledge that it may be
different from the sample mean
– assume it is 4.5
 What is the difference between 4.5 and 4.0?
Errors in Research design
 Sampling errors – difference between measure
obtained from the sample and true measure
obtained from the population from which the
sample is drawn (assuming random sampling is
used)
 Non-sampling errors
–
–
–
–
Design errors
Administering errors
Response errors
Non-response errors
Non-sampling errors – Design Errors
 Selection errors – biased sample selection
 Population specification error – drawing a
sample from the wrong population
Non-sampling errors – Design Errors
 Sampling frame error – using inaccurate
sampling frame to create the sample
 Surrogate information error – difference
between information required for the study
and what the researcher seeks
Non-sampling errors – Design Errors
 Measurement error – difference between
information sought by the researcher and
information generated by a particular
measurement procedure used by the
researcher
Non-sampling errors – Design Errors
 Experimental error – improper experimental
design
 Data Analysis error – e.g. wrong data coding
or wrong statistical analysis
Non-sampling errors – Administering
Errors
 Questioning error – incorrect phrasing of
questions to respondents
 Recording error – improperly recording the
respondents answers
 Interference error – does not follow the
exact procedure while collecting data
Non-sampling errors – Response
Errors
 Respondent supplies (intentionally or
unintentionally) incorrect answers to
questions
– Does not understand the question
– “Fatigue or boredom
Non-sampling errors – Response
Errors
 Unwillingness to give information
 Social desirability bias
Non-sampling errors –
Non-Response Errors
 Respondents who did not respond may think
differently on the issue
 Some members of the sample may have
provided incomplete information
RESEARCH DESIGN PROCESS
Compare Cost and Timing Estimates with
Anticipated Value
Revise
Terminate
Implementation
Proceed
Data Collection and Analysis
Data collection
Field work
Data processing
Data analysis
Statistical analysis
Interpretation
Conclusions and Recommendations