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In an experiment,….
the researcher manipulates one or more independent variables to determine the effect on a dependent variable.
Independent variable
The purported cause of a causal hypothesis, on which the dependent variable may depend.
Dependent variable
the variable that is acted upon, or the outcome the researcher seeks to understand.
Experimental group
The groups that is exposed to the experimental manipulation
Control group
The group that is not exposed to the manipulation of the independent variable.
Random assignment
The process of randomly assigning participants to different groups in an experiment to ensure that each participant has an equal chance of being placed in any group, thereby minimizing bias.
Causality
Refers to a relationship in which one factor or variable is dependent on another factor or variable
Spuriousness
A condition when the apparent relation between two concepts is actually the result of some third concept, or confound, influencing both of them
Laboratory experiments
take place in laboratories where researchers are given the maximum amount of control over the environment in which the experiment is conducted
Double-blind study
A study in which neither the researcher not the participant is aware of which condition the participant is in. (also helps address the Hawthorne effect)
Experimenter effects
occur when a researcher subtly or unconsciously affects the performance of a study participant.
Field experiment
Takes place in a natural or real-world setting and are often used to evaluate the success of interventions to improve educational and health outcomes.
Audit study
Type of field experiment used to assess whether characteristics such as gender, race, and sexual orientation lead to discrimination in real labor and housing markets.
Factorial design experiements
Have two or more independent variables. This allows researchers to measure various characteristics at once.
Population-based experiments
rely on survey methods and are conducted on a representative sample of the population of interest
Natural Experiment
The independent variable is manipulated by “nature”, not by the experimenter
Cover story
Researchers use to keep participants engaged without revealing the study’s true purpose
Confederates
Individuals who are trained to pretend to be study participants
Between-subject design
participants are randomly assigned to different levels of the independent variable
within-subject design
participants receive all levels of the independent variable
Behavioral measures
measures collected by observing the overt and observable actions of participants
Attitudinal measures
Self-reported responses of participants to questions about their attitudes, opinions, emotions, and beliefs
Physiological measures
Biological responses to stimuli
Debrief
when participants have been given a false rationale for the study it is important to tell them the true purpose of the study
Survey
a social research method in which researchers ask a sample of individuals to answer a series of questions
Closed-ended questions
fixed response options
Primary data collection
occurs when social researchers design and carry out their own data collection
Secondary data
a resource that was collected by someone else
Self administered questionnaire (SAQ)
A survey completed directly by respondents through the mail or online
Mode of administration
the way the survey is administered (e.g., as face-to-face, by phone or mail, or online
Response categories
the preset answers on a survey
Cross-sectional surveys
surveys for which data are collected at only one time point
Longitudinal survey
studies in which data are collected at multiple time points
Repeated cross-sectional surveys
Type of longitudinal surveys where data is collected at multiple time points but from different subjects at each time point
Panel surveys
Type of longitudinal surveys where data is collected on the same subjects at multiple time points
Nonresponse
-Respondents may choose not to participate in a survey at all or
not to respond to particular questions on the survey.
-If individuals who do and do not respond differ in systematic
ways, then the results of the study may be biased
Measurement error
-It occurs when the approach used to measure a particular
variable affects the response provided.
-It may include the survey design, the interviewer, or the setting.
Coverage error
-The sampling frame does not adequately capture all members of
the target population.
-It results from either systematically omitting respondents or
including the same respondents multiple times.
Sampling error
-It involves differences between the characteristics of the sample
and the characteristics of the population that the sample
represents.
paper-and-pencil interview (PAPI)
where the researcher asks questions and records
the respondent’s answers in a preprinted copy of the survey booklet
Showcards
used to aid respondents on questions for which there are many response categories.
Audio computer-assisted self-interview (ACASI)
an
innovative technology designed to facilitate the self-administered
component of the face-to-face interview.
Social desirability bias
respondents may report socially valued behaviors and attitudes in the survey setting.
dichotomous outcome
requires a simple “yes” or “no” answer
Likert scale
captures the respondent’s level of agreement or disagreement with a statement.
forced-choice
questions regarding agreeing or disagreeing produce the best quality data
acquiescence bias
where respondents tend to answer “agree”
index
a sum of responses to multiple survey items that capture a particular concept being measured
scale
averages the responses to multiple items that capture a particular concept
Order effects
occur when the order in which questions appear biases the responses
Priming effects
are a type of order effect in which exposure to a particular image, word, or feeling shapes how respondents think and feel in the immediate aftermath
pretest
is a trial run of a survey administered to a group of
people who are similar to the study sample
Frequency distributions
help researchers assess problems with the questions, such as a large percentage of respondents choosing the answer, “I don’t know.”
samples
subsets of a population selected for a study
target population
The population being studied
Sampling
the process of deciding what or whom to observe
when you cannot observe and analyze everything or everyone
probability sample
A sample chosen via random selection with two key characteristics. One is random chance is used to select participants for the sample. Second is each individual has a probability of being selected that can be calculated
census
a study that includes data on every member of a population, as opposed to only a sample
population parameter
a number that characterizes some quantitative aspect of a population
convenience sample
which the cheapest and easiest observations are selected
systematic error
a flaw built into the design of the study that causes a sample estimate to diverge from the population parameter.
margin of error
the amount of uncertainty in an estimate; equal to the distance between the estimate and the boundary of the confidence interval
sampling distribution
a set of estimates that would be observed from a large number of independent samples that are all the same size and drawn using the same method
Confidence levels
he probability that an estimate includes the
population parameter.
confidence interval
The range implied by the margin of error
sampling frame
a list of population members from which a probability sample is drawn
simple random sample
a type of probability sample in which each individual/unit has the same probability of being selected.
systematic sample
a probability sampling strategy in which sample members are selected by using a fixed interval.
Cluster samples
a probability sampling strategy in which researchers divide up the target population into groups, or “clusters.”
Stratified sampling
a probability sampling strategy in which the population is divided into groups, or strata
oversample
a group that is likely to be underrepresented in a simple random sample
variable-oriented research
scientists study a large number of cases, but gather only a limited amount of data (or variables) about each.
case-oriented research
scientists gather large amounts of data about a single case or small number of cases
Purposive sampling
a sampling strategy in which cases are selected on the basis of features that distinguish them from other cases
deviant cases
cases that are unusual, unexpected, or hard to explain given what is currently known about a topic.
Sequential sampling
a sampling strategy in which researchers make decisions about what additional data to collect based on their findings from data they’ve already collected
Key informants
the first point of contact a researcher has with
his or her study population.
Snowball sampling
a strategy in which the researcher starts with one respondent who meets the requirements for inclusion and asks him or her to recommend other people to contact
Big data
includes data sets with billions of pieces of information, typically created through individuals’ interactions with technology.
administrative records
which include data collected by government agencies or corporations as part of their own record-keeping
