Exam 2 Flashcards
Open-sourced questions
Allows respondents to answer in any way they like
Forced choice questions
People giving their opinions by choosing the best of two or more options
Likert Scale
Presented with a statement and then asked how they would indicate their degree of agreement
Semantic differential format
Respondents asked to rate a target object using a numeric scale that is anchored with adjectives
Leading Questions
Framing a question as positive or negative will lead an answer that will give an answer that goes along with the wording of the question
Negatively worded question
Unnecessarily complicated questions that can cause cognitive difficulty for people
Response sets/nondifferentiation
Type of shortcut respondents can take when answering survey questions
Acquiescence/yea-saying
Respondents say yes to something without reading the question carefully (reason for including inverse worded questions)
Fence sitting
Playing it safe and answering all of the questions in the middle (this may be a reason to include even numbered questions.
Socially desirable responding/faking good
Because a respondent is shy, embarrassed or worried about answering wit an unpopular opinon, they will not tell the truth on a survey or another self-report measure. A similar problem would be faking bad
Observational Research
A researcher watches people or animals and systematically records what they are doing
Observer Bias
When the observers’ expectation influence their interpretation of the participants behavior in the outcome of the study
Masked Design/Blind design
When observers are unaware of the conditions to which participants have been assigned and unaware of what the study is about
Generalizability
Does the sample represent the population
Population
The entire set of people or products in which you are interested in
Sample
A smaller set of the population
Census
A survey of the entire population
Population of interest
The population that the researchers want to generalize
Biased sample/unrepresented sample
Members of the population of interest have a much higher probability of being included in the sample compared to other members
Representative sample/unbiased sample
All members of the population have an equal chance of being included in the sample
Convenience sampling
Using a sample of people who are readily available to participate
Self-selection
When a sample is known to contain only people who volunteer to participate
Simple Random Sampling
A hat with tickets in it
Cluster sampling
Clusters of participants within a population of interest are randomly selected, then all individuals in each selected cluster are used
Multistage sampling
Two random samples are selected: a random sample of clusters and then a random set of people within clusters
Stratified random sampling
The researcher selects particular demographic categories on purpose and then randomly selects individuals within each of the categories
Oversampling
The researcher intentionally over represents one or more groups
Systematic sampling
Using a computer or a random number table, the researcher selects a random number then counts off
Random assignment
Only in experimental designs, researchers place participants into different groups and are assigned at random
Purposive Sampling
When researchers only want to study certain kinds of people and only recruit those particular participants
Snowball sampling
Participants are asked to recommend people to the study
Quota sampling
The researcher identifies subsets of the population of interest and then sets a target number for each category in the sample
Bivariate correlation/bivariate associationn
An association that involves exactly two variables
Categorical variable
The value falls in either one category or another
Quantitative variable
The value of 7 means more than 6, 6 means more than 5 and so on
T test
When testing associations and only one variable is categorical
Effect size
Describes the strength of an association
Statistical significance
The conclusion a researcher reaches regarding how likely it is they’d get a correlation of that size just by chance, assuming there’s no correlation in the real world
Outlier
An extreme score that stands out over the pack
Restriction of range
If there is not a full range of scores on one of the variables in the association, it can make the correlation appear smaller than it really is
Curvilinear association/curvilinear correlation
The relationship between two variables that is not a straight line
Causal temptation
The powerful automatic tendency to make a causal inference from any association claim we read
The three causal criteria
Covariance of the cause and effect, temporal precedence, Internal validity
Covariance of cause and effect
There must be a correlation, or association between the cause variable and the effect variable
Temporal precedence
The causal variable must precede the effect variable; it must come first in time
Internal validity
There must be no plausible alternative explanations for the relationship between the two variables
Directionality problem/temporal precedence
We don’t know which variable came first
Third-variable problem
When we can come up with an alternative explanation for the association between two variables, that alternative explanation is the third variable
Moderator
When the relationship between two variables changes depending on the level of another variable, that other variable is the moderator
Covariance
The two variables are clearly related
Temporal precedence
Ability to show which variable comes first
Internal validity
Is it more likely to be explained by a third variable?
Longitudinal design
Measuring the same variables in the same people at several points in time
Cross-sectional correlations
Testing to see whether two variables, measured at the same point in time are correlated
Autocorrelations
They determine the correlation of one variable with itself, measured on two different occasions
Cross-lag correlations
Show whether the earlier measure of one variable is associated with the later measure of the other variable- researchers are most interested in this
Parsimony
The degree to which a good scientific theory provides the simplest explanation of some phenomenon
Mediator/mediating variable
The explanations for causal relationships- only established when the proposed causal variable is measured first in a study and then is followed by the mediating variable, and the followed by the proposed outcome variable
Survey/Poll
A method of answering questions to people, whether on the phone, in person, written questionnaires or online
