Basic HTML Version
© 2014 Pacific Crest
207
S
trategies
A
nalyzing
N
ewly
G
enerated
D
ata
by
T
ype
Step
Explanation
1.
Purpose
What is the purpose? Define the purpose.
Survey
Experiment
Transaction
Observation
Learn something
important
To test a hypothesis
Describe the nature of
the transaction
What and why are we
observing
2.
Context
What is the depth and breadth of the project?
Survey
Experiment
Transaction
Observation
Unique characteristics
of the population in a
particular situation
The number of trials that
will be run to test the
hypothesis
Number of
total transac-
tions/site/time period
(may also be a single
transaction that involves
multiple parties)
Who is going to be
observed for how long
3.
Fields
What are the variables to be collected?
Survey
Experiment
Transaction
Observation
Data to be collected
Experimental design
elements
Pertinent data to
characterize the
transaction
Occurrences, events, or
changes
4.
Domains
What are acceptable values?
Survey
Experiment
Transaction
Observation
The range of acceptable
responses defined in the
instructions
The minimum and
maximum potential
readings from the
experiment
Lookup tables
Do your observations
make sense for the
current context?
5.
Iteration
What causes a next iteration?
Survey
Experiment
Transaction
Observation
participant
trial
each instance
new event to be
observed
6.
Collection means
How is the data captured? What tool is used?
Survey
Experiment
Transaction
Observation
Printed, oral, or online
survey form
Visual measuring and
recording in a lab jour-
nal; automatic recording
with instruments
Computer capturing
package of data, forms,
and logs
Collection form, video,
audio recording, photos/
pictures
7.
Error checking
How to catch and correct errors
Survey
Experiment
Transaction
Observation
Use redundant
questions worded
differently;
only accept answers
from given values
Repeated
experiments should
produce the same
results; check for
recording errors
Identify/locate any
missing transaction
data; use of lookup
tables
Checking for bias and
reasonableness
5.1 Data Generation