Transcript Data Collection and Analysis

Chapter Four
Research Design and
Implementation - 2
Essentials of Marketing Research
Kumar, Aaker, Day
Four types of Data
 Alphabetical / Categorical / Nominal data:
– Information falls only in certain categories, not
in-between categories
– No inferences possible between groups
– Only reporting frequencies, percentages and
mode makes sense (descriptive statistics)
– Chi Square measure of Association (inferential
Statistics)
– Examples: gender, age groups, income groups,
etc.
Essentials of Marketing Research
Kumar, Aaker, Day
Four types of data
 Rank order data:
– Ranked according to some logic, e.g. preference,
etc.
– Again an in-between rank does not make sense.
– Difference between say rank 1 and 2 need not
necessarily be of the same magnitude as the
difference between rank 3 and 4.
– Only reporting frequencies, percentages and mode
makes sense (descriptive statistics); Spearman Rho
coefficient of correlation (Inferential statistics)
– Examples: brand preferences, class rank on test,
etc.
Essentials of Marketing Research
Kumar, Aaker, Day
Four types of data
 Interval Level
– Numerical data in which the numbers denote the
amount of presence / absence of a trait.
– zero point does not necessarily mean complete
absence of the trait
– In-between numbers make sense
– Magnitude of difference between numbers of the
scale is constant.
– All descriptive and inferential statistics possible
– Examples: attitude, satisfaction, temperature, etc.
Essentials of Marketing Research
Kumar, Aaker, Day
Four types of data
 Ratio level data
– Interval level data with a meaningful zero point
meaning complete absence of the trait
– Magnitude of the difference between numbers
of the scale is constant AND the zero point
denotes complete absence of the trait being
measured.
– All descriptive and inferential statistics possible
– Examples: sales, profits, weight, height, etc.
Essentials of Marketing Research
Kumar, Aaker, Day
Type of data?
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
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?
Essentials of Marketing Research
Kumar, Aaker, Day
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 assume that it is different from
the sample mean
– assume it is 4.5
 The difference of 0.5 (4.5 – 4.0) is the total
error in the research design
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
Non-sampling errors – Design Errors
 Selection errors – biased sample selection
 Population specification error – drawing a
sample from the wrong population
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
Non-sampling errors – Design Errors
 Experimental error – improper experimental
design
 Data Analysis error – e.g. wrong data coding
or wrong statistical analysis
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
Non-sampling errors – Response
Errors
 Respondent supplies (intentionally or
unintentionally) incorrect answers to
questions
– Does not understand the question
– “Fatigue or boredom
Essentials of Marketing Research
Kumar, Aaker, Day
Non-sampling errors – Response
Errors
– Unwillingness to give information
– Social desirability bias
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing Research
Kumar, Aaker, Day
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
Essentials of Marketing
Research
Conclusions
and Recommendations
Kumar, Aaker, Day