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Exam2

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QuestionAnswer
Experiment Research approach in which one variable is manipulated and the effect on another variable is observed.
Causal Research Research designed to determine whether a change in one variable likely caused an observed change in another.
Concomitant Variation Statistical relationship between two variables.
Appropriate Time Order of Occurrence Change in an independent variable occurred before an observed change in the dependent variable.
Field experiments Tests conducted outside the laboratory in an actual environment, such as a marketplace.
Laboratory experiments Experiments conducted in a controlled setting.
Internal validity Extent to which competing explanations for the experimental results observed can be ruled out.
External validity Extent to which causal relationships measured in an experiment can be generalized to outside persons, settings, and times.
History Intervention, between the beginning and end of an experiment, of outside variables or events that might change the dependent variable.
Maturation Changes in subjects occurring during the experiment that are not related to the experiment but which may affect subjects' response to the treatment factor.
Instrument variation Changes in measurement instruments that might affect measurements.
Selection bias Systematic differences between the test group and the control group due to a biased selection process.
Mortality Loss of test units or subjects during the course of an experiment, which may result in a nonrepresentativeness.
Testing effect Effect that is a by-product of the research process itself.
Regression to the mean Tendency of subjects with extreme behavior to move toward the average for that behavior during the course of an experiment.
Randomization Random assignment of subjects to treatment conditions to ensure equal representation of subject characteristics.
Physical control Holding constant the value or level of extraneous variables throughout the course of an experiment.
Design control Use of the experimental design to control extraneous causal factors.
Statistical control Adjusting for the effects of confounded variables by statistically adjusting the value of the dependent variable for each treatment condition.
Experimental design Test in which the researcher has control over and manipulates one or more independent variables.
Treatment variable Independent variable that is manipulated in an experiment.
Experimental effect Effect of the treatment variable on the dependent variable.
Contamination Inclusion in a test of a group of respondents who are not normally there - e.g.; buyers from outside the test market who see an advertisement intended only for that hose in the test area and enter the area to purchase the product being tested.
Pre-experimental designs Designs that offer little or no control over extraneous factors.
One-shot case study design Pre-experimental design with no pretest observations, no control group, and an after measurement only.
One-group pretest-posttest design Pre-experimental design with pre- and postmeasurements but no control group.
True experimental design Research using an experimental group and a control group, to which test units are randomly assigned.
Before and after with control group design True experimental design that involves random assignment of subjects or test units to experimental and control groups and pre- and postmeasurements of both groups.
after-only with control group design True experimental design that involves random assignment of subjects or test units to experimental and control groups, but no premeasurements of the dependent variable.
Quasi-experiments Studies in which the researcher lacks complete control over the scheduling of treatments or must assign respondents to treatments in a nonrandom manner.
Interrupted time-series design Research in which repeated measurement of an effect interrupts previous data patterns.
Multiple time-series design Interrupted time-series design with a control group.
Test market Real world testing of a new product or some element of the marketing mix using an experimental or quasi-experimental design.
Measurement Process of assigning numbers or labels to persons, objects, or events in accordance
Rule Guide, method, or command that tells a researcher what to do.
Scale Set of symbols or numbers so constructed that the symbols or numbers can be assigned by a rule to the individuals to whom the scale is applied.
Nominal scales Scales that partition data into mutually exclusive and collectively exhaustive categories.
Ordinal scales Scales that maintain the labeling characteristics of nominal scales and have the ability to order data.
Interval scales Scales that have the characteristics of ordinal scales, plus equal intervals between points to show relative amounts; they may include an arbitrary zero point.
Ratio scales Scales that have the characteristics of interval scales, plus a meaningful zero point so that the magnitudes can be compared arithmetically.
Reliability Degree to which measures are free from random error and therefore provide consistent data.
Test-retest reliability Ability of the same instrument to produce consistent results when used a second time under conditions as similar as possible to the original conditions.
Stability Lack of change in results from test to retest.
Equivalent form reliability Ability of two very similar forms of an instrument to produce closely correlated results.
Internal consistency reliablity Ability of an instrument to produce similar results when used on different samples during the same time period to measure a phenomenon.
Split-half technique Method of assessing the reliability of a scale by dividing the total set of measurement items in half and correlation the results.
Validity Degree to which what the researchers was trying to measure was actually measured.
Face validity Degree to which a measurement seems to measure what it is supposed to measure.
Content validity Representativeness of the content of the measurement instrument.
Criterion-related validity Degree to which a measurement instrument can predict a variable that is designated a criterion.
Predictive validity Degree to which a future level of a criterion variable can be forecast by a current measurement scale.
Concurrent validity Degree to which another variable, measure at the same point in time as the variable of interest, can be predicted by the measurement instrument.
Construct validity Degree to which a measurement instrument represents and logically connects, via the underlying theory, the observed phenomenon to the construct.
Convergent validity Degree of correlation among different measurement instruments that purport to measure the same construct
Discriminant validity Measure of the lack of association among constructs that are supposed to be different.
Scaling Procedures for assigning numbers to properties of an object in order to impart some numerical characteristics to the properties in a question.
Unidimensional scales Scales designed to measure only one attribute of a concept, respondent, or object.
Multidimensional scales Scales designed to measure several dimensions of a concept, respondent, or object.
Graphic rating scales Measurement scales that include a graphic continuum, anchored by two extremes.
Itemized rating scales Measurement scales in which the respondent selects an answer from a limited number of ordered categories.
Noncomparative scales Measurement scales in which judgment is made without reference to another object, concept, or person.
Q-sorting A measurement scale employing a sophisticated form of rank ordering using card sorts.
Paired comparison scales Measurement scales that ask the respondent to pick one of two objects in a set, based on some stated criteria.
Constant sum scales Measurement scales that ask the respondent to divide a given number of points among two or more attributes, based on their importance.
Semantic differential scales Measurement scales that examine the strengths and weaknesses of a concept by having the respondent rank it between dichotomous pairs of words or phrases that could be used to describe it; the means of the responses are then plotted as a profile, or image.
Stapel scales Measurement scales that require the respondent to rate how closely and in what direction a descriptor adjective fits a given concept.
Likert scales Measurement scales in which the respondent specifies a level of agreement or disagreement with statements expressing either a favorable or unfavorable attitude toward the concept under study.
purchase intent scales Scales used to measure a respondent's intention to buy or not buy a product.
Net Promoter Score Begins with a 10 point scale on likelihood to recommend. Then, the differences between promoters and dissuaders is computed.
Balanced scales Measurements scales that have the same number of positive and negative categories.
Nonbalanced scales Measurement scales that are weighted toward one end or the other.
Determinant attitudes Those consumer attitudes most closely related to preferences or to actual purchase decisions.
Questionnaire Set of questions designed to generate the data necessary to accomplish the objectives of the research project; also called an interview schedule or survey instrument.
Editing Going through each questionnaire to ensure that skip patterns were followed and the required questions were filled out.
Skip pattern Sequence in which questions are asked, based on a respondent's answer.
Coding Process of grouping and assigning numeric codes to the various responses to a question
Survey Objectives Outline of the decision-making information sought through the questionnaire
Open-ended questions Questions to which the respondent replies in her or his own words
Closed-ended questions Questions that require the respondent to choose from a list of answers
Dichotomous questions Closed-ended questions that ask the respondent to choose between two answers.
Multiple-choice questions Closed-ended questions that ask the respondent to choose among several answers
Scaled-response questisons Closed-ended questions in which the response choices are designed to capture the intensity of the respondent's feeling.
Clarity in wording Avoid ambiguous terminology, use reasonable, vernacular language adjusted to the target group, as only one question at a time.
Respondent biasing Leading questions that give away the research goal or sponsor identity.
Screeners Questions used to identify appropriate respondents
Prompters Short encouraging statements to rebuild respondent interest
Necessary questions Pertain directly to the stated survey objectives or are screeners, interest generators, or required transitions.
Approval by managers Managerial review and approval after questionnaire drafting to prevent false starts and expensive redrafts.
Pretest Trial run of questionnaire
Supervisor's instructions Written directions to the field service firm on how to conduct the survey.
Field management companies Firms that provide such support services as questionnaire formatting, screener writing, and coordination of data collection.
Questionnaire costs and profitablity Factors affecting costs and profits include overestimating, overbidding, incidence rate, roadblocks to completed interviews, and premature interview terminations.
Sampling Process of obtaining information from a subset of a larger group
Population Entire group of people about whom information is needed
Census Collection of data obtained from every member of the population of interest
Sample Subset of all members of a population of interest
Sampling frame List of population elements from which units to be sampled can be selected or a specified procedure for generating such a list
Random-digit dialing Method of generating lists of telephone numbers at random
Probability samples Samples in which every element of the population has a known, nonzero likelihood of selection
Nonprobability samples Samples in which specific elements from the population have been selected in nonrandom manner
Sample size The Identified and selected population subset for the survey, chosen because it represents the entire group
Population parameter A value that accurately portrays or typifies a factor of a complete population, such as average age or income
Sampling error Error that occurs because the sample selected is not perfectly representative of the population
Nonsampling error All error other than sampling error; measurement error
Simple random sample Probability sample selected by assigning a number to every element of the population and then using a table of random numbers to select specific elements for inclusion in the sample.
Systematic sampling Probability sample in which the entire population is numbered and elements are selected using a skip interval
Stratified sample Probability sample that is forced to be more representative through simple random sampling of mutually exclusive and exhaustive subsets
Proportional allocation Sampling in which the number of elements selected from a stratum is directly proportional to the size of the stratum relative to the size of the population.
Disproportional allocation Sampling in which the number of elements taken from a given stratum is proportional to the relative size of the stratum and the standard deviation of the characteristic under consideration.
Cluster sample Probability sample in which the sampling units are selected from a number of small geographic areas to reduce data collection costs
Multistage area sampling Geographic areas selected for national or regional surveys in progressively smaller population units, such as counties, then blocks, then homes.
Convenience samples Nonprob. samples based on using people who are easily accessible
Judgment samples Nonprob. samples in which the selection criteria are based on the researcher's personal judgment about representativeness of the population under study.
Quota samples Nonprob. samples in which quotas based on demographic factors selected by the researcher, are established for population subgroups.
Snowball samples Nonprob. samples in which additional respondents are selected based on referrals from initial respondents.
Created by: srgrant on 2012-10-22



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