141 Exam 1 Flashcards
Site analysis techniques
Techniques using secondary data to select best location for retail or wholesale operation
Index of retail saturation
Calculation describing relationships between retail demand and supply as ratio of sales potential per unit area of retail space
Data mining
Use of powerful computer analytical routines to dig through volumes of data searching for patterns
Neural networks
AI in which computer is programmed to mimic human brains processing information
Market based analysis
Data mining analyzing anonymous point of sale transaction databases to id coinciding purchases between products purchases and retail shopping info
Customer discovery
Involves mining data to look for patterns iding who is likely to be a valuable customer
Database marketing
Use of customer data to promote one on one relationships with customers and precisely target promos
Internal data
Data officiating in organizations and represent events recorded or generated by organizations
Proprietary data
Secondary data owned and controlled by organizations
Enterprise search
Search driven by internet type search engine focusing on data within organizations internal network
External data
Facts observed recorded and stored by an entity outside researchers organization
Respondents
Answer interview questions verbally or written question through any media delivery
Sample survey
Formal term for survey emphasizing respondents opinions represent larger target populations opinions
Sample error
Error arising because inadequacies of actual respondents to represent population of interest
Systematic error
Some imperfect aspect of research design causes respondents error or a mistake in execution of research
Population parameter
True value of a phenomenon within population
Respondent error
Respondent lying Or no response
Nonresponse error
Statistical difference b/w survey that includes only those who respond and a perfect survey would also include a list of who didn’t
Acquiescence bias
Tendency to maintain response style agreeing with viewpoints of the survey
Item nonresponse
Failure of respondent to provide answer to survey question
CATI
Computer assisted telephone interviews
Robocalls
Call conducted by auto dialed using recorded message
Coverage bias
Misrepresentation of population by survey results disproportionately represent one group over another
Random digit dialing
Telephone exchange and random numbers develop sample of respondents in landline survey
Crowdsourcing
Many many people invited to participate in project via internet or social networks, even a small % of completes generates a large sample
Pretesting
Screening procedure to iron out fundamental problems in survey design
Observer bias
Distortion resulting from cognitive behavior or action of a witnessing observer
Contrived observation
Artificial environment to test a hypothesis
Response latency
Time taken to chose between alternatives. Measures strength of preference
Artifacts
Things made and consumed within culture signaling something meaningful about behavior occurring
Portable people meter 360 PPM360
Small cellphone automatically detects broadcast signals, satellite radio, and tv transmissions
Pupilometer
Device record changes in diameter of subjects pupils
Eye tracking monitor
Observes eye movements, some monitors use infrared to measure unconscious eye movement
Psycho galvanometer
Measures galvanic skin response, electrical resistance of skin
Voice pitch analysis
Records abnormal frequencies in voice that reflect emotional reactions
Subjects
Sampling units for experiment
Experimental conditions
One possible levels of an experimental variable manipulation
Blocking variables
Categorical variables, way of statistically controlling variance
Covariate
Continuous variable included in statistical analysis as a way of controlling variance
Main effect
Difference in dependent variable means between the different levels of any single experimental variable
Interaction effects
Differences in dependent variable due to specific combination of independent variables
Cell
Specific treatment combination associated with experimental group
Test units
Subjects or entities whose responseto the experimental treatment are measured or observed
Randomization
Random assignment of subject and treatments to groups
Repeated measures
Subjects is exposed to multiple treatments
Confound
Alternative explanation beyond variables for any observed differences in dependent variable
Demand characteristic
Experimental design elements or procedure unintentionally provides subjects with hints about hypothesis
Demand effect
When demand characteristic actually affect dependent variable
Dependent variable (criterion)
The thing we are trying to indirectly change
Independent variable (predictor)
The thing we control to change the criterion (treatment)
Counterbalancing
Eliminate confounding effects of order of presentation. 1/4th exposed to A first, 1/4th to B first, 1/4th to C first, and 1/4th to D first
Tachistoscope
Time subject is exposed to visual image
Within subject design
Repeat measurements because each treatment measures the same subject
Between subject design
Each subject receives only one treatment combo
Manipulation check
Makes sure manipulation does produce differences in independent variable
History effect
Some change other than experimental treatment occurs during course of experiment that affects dependent variables
Cohort effect
Change in dependent variable occurring because member of one group experienced different historic situations than members of another group
Maturation effect
Time and naturally occurring events coincide with growth and experience
Testing effects
Effects when initial measurements or tests primes subjects in a way that affects response
Instrumentation effect
Change in wording of question, change in interviewers, or other procedure cause change in dependent variable
Mortality effect
Subjects withdraw from experiment before its done
External validity
Accuracy with which experimental results can be generalized beyond subjects
Internal validity
Exists to the extent that an experimental variable is truly responsible for any variance in dependent variable
Attention filters
Items that have known and obvious answer Included just to see if participants are playing along
Test market sabotage
Intentional attempts to disrupt the results of a test-market being conducted by another firm
Lab experiments
More control over research setting and extraneous variables
Field experiments
Involve experimental manipulation that are implemented in natural environments
Consistency of conditions
Subjects in all groups exposed to identical conditions except for differing treatments
Placebo
False treatment disguising the fact no real treatment is administered
Placebo effect
Effect in dependent variable associated with psychological impact along with knowledge of some treatment being administered
Systematic or nonsampling error
Occurs if sampling units in experimental cell are some how different than units in another cell and this affects the dependent variables
Experimental Group
Subjects who a treatment is administered to
Control group
Subjects whom no experimental treatment is administered, serves as baseline for comparison
Experimental treatment
The way an experimental variable is manipulated
