381 Quiz 5 Study

Front 1

basic science

Back 1

accumulates empirically verifiable facts about the world and its inhabitants

Front 2

applied science

Back 2

puts a premium on knowledge that is more immediately useful

Front 3

3 basic ethical principles

Back 3

respect for persons, beneficence, and justice

the commision found a way to apply all 3:
1. the requirement of full and informed consent
2. a formal assessment of the risk and benefits of research participation
3. a system of distributive justice in the selection of research participants (which includes types of groups)

Front 4

respect for persons (ethical principle 1)

Back 4

people are capable of forming their own opinions, making choices and carrying out actions...treat everyone as an autonomous agent with freedom of action

Investigators should provide additional protection to individuals with special circumstances

Front 5

beneficence (ethical principle 2)

Back 5

investigators are obliged to avoid harming individuals who participate in research
In cases where the research involves some level of risk, it is the investigators duty to minimize these risks and to max all possible benefits for the participant

Front 6

justice (ethical principle 3)

Back 6

investigators must take care to distribute the advantages and disadvantages of research participation in a balanced manner, so that no particular group reaps greater benefits or suffers greater burdens

Front 7

Validity

Back 7

How well measure or design does what it says it does
Validity is about logic of study: does it make sense?

Front 8

Reliability

Back 8

A measure is stable or consistent
Reliability is more numerical: do measures meet established standards in the field?

Front 9

Construct validity

Back 9

are the variables operationalized appropriately?

measures what it’s supposed to measure

Front 10

statistical validity

Back 10

are the data analyzed properly?

Front 11

internal validity

Back 11

is the independent variable actually the cause of differences in the dependent variable?

Front 12

external validity

Back 12

does this study generalize to other people, situations, locations, etc.?

Front 13

test-retest reliability

Back 13

temporal stability

the variation in measurements taken by a single person or instrument on the same item and under the same conditions. A less-than-perfect test-retest reliability causes test-retest variability. Such variability can be caused by, for example, intra-individual variability and intra-observer variability. A measurement may be said to be repeatable when this variation is smaller than some agreed limit.

is an estimate of the degree of fluctuation of the instrument, or
of the characteristic it is designed to. measure, from one administration to another.

Front 14

alternate-form reliability

Back 14

equivalence

An alternate form reliability is the authenticity stablished by carrying out two different forms of the same test to the same individuals. This method is convenient to avoid the problems that come from the test-retest method. With the alternate form reliability method, an individual is tested on one form of the test, and then again on a comparable second form, the inbetween time is about one week. This method is used more than the test-restest method because it has fewer related problems, including an abundance reduction in practice effects

In this experiment, two roles were given to the participants, either the role of a prisoner or a prison guard. If both roles were given to the same participant then this would have been an example of an alternate form reliability, but since the roles are given to different participants, the term does not apply to the experiment. If this concept is used correctly, a participant would be given the roles of both a prison guard and a prisoner, later, that individuals behavior during that role would be compared to the other. Since both roles are not predicted to be similar, this is the reason why alternate form reliability was not used in this experiment.

Front 15

convergent validity

Back 15

matches

, a parameter often used in sociology, psychology, and other behavioral sciences, refers to the degree to which two measures of constructs that theoretically should be related, are in fact related.[1] Convergent validity, along with discriminant validity, is a subtype of construct validity. Convergent validity can be established if two similar constructs correspond with one another, while discriminant validity applies to two dissimilar constructs that are easily differentiated.

Front 16

discriminant validity

Back 16

different

tests whether concepts or measurements that are supposed to be unrelated are, in fact, unrelated

Front 17

content validity

Back 17

samples relevant material, e.g. quizzes

refers to the extent to which a measure represents all facets of a given social construct. For example, a depression scale may lack content validity if it only assesses the affective dimension of depression but fails to take into account the behavioral dimension. An element of subjectivity exists in relation to determining content validity, which requires a degree of agreement about what a particular personality trait such as extraversion represents. A disagreement about a personality trait will prevent the gain of a high content validity

Front 18

criterion validity

Back 18

correlated with outcome criteria

a measure of how well one variable or set of variables predicts an outcome based on information from other variables, and will be achieved if a set of measures from a personality test relate to a behavioral criterion on which psychologists agree.

Front 19

Concurrent validity

Back 19

present

is demonstrated where a test correlates well with a measure that has previously been validated. The two measures may be for the same construct, or for different, but presumably related, constructs

Front 20

Predictive validity

Back 20

future

the extent to which a score on a scale or test predicts scores on some criterion measure

Front 21

Known groups validity

Back 21

inter-rater?

Front 22

face validity

Back 22

does it appear to measure what it should?

the term simply means whether the test seems on the surface
(or "face") to be measuring something relevant. It should not be confused
with content validity, as face validity refers not to what the tesr measures but only
to how it looks. The idea of face validity is that if a test does not appear to be relevant,
some respondents may not take it seriously

Front 23

how all the items in the test hang together

Back 23

its internal-consistency reliability),

reliability of components

Front 24

systematic error

Back 24

is the name for fluctuations that are not random
but are slanted in a particular direction (thus, another name for systematic
error is btas)

Front 25

random error

Back 25

(often described as noise) is the name for chance fluctuations, or haphazard errors.

Front 26

temporal stability

Back 26

or dependability in this example,
we mean that those who scored high initially scored high on retest, and
that those who scored low initially scored low on retest.

Front 27

item to item reliability

Back 27

Think of this value as the estimate of the reliability of
any single item on average.

Front 28

questionnaire

Back 28

the physical instrument used for data collection

Front 29

survey

Back 29

a type of study designed to collect information from a sample in order to generalize to a population
The quality of a survey is defined by its sampling
What makes a good sample?
How important is representativeness?
How important is sample size?

Front 30

simple random sample

Back 30

a subset of individuals (a sample) chosen from a larger set (a population).

Front 31

stratified random sample

Back 31

when subpopulations within an overall population vary, it is advantageous to sample each subpopulation (stratum) independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should be mutually exclusive: every element in the population must be assigned to only one stratum. The strata should also be collectively exhaustive: no population element can be excluded. Then simple random sampling or systematic sampling is applied within each stratum. This often improves the representativeness of the sample by reducing sampling error. It can produce a weighted mean that has less variability than the arithmetic mean of a simple random sample of the population.

Front 32

cluster sampling

Back 32

used when "natural" but relatively homogeneous groupings are evident in a statistical population. It is often used in marketing research. In this technique, the total population is divided into these groups (or clusters) and a simple random sample of the groups is selected. Then the required information is collected from a simple random sample of the elements within each selected group.

Front 33

response order effects: auditory

Back 33

recency

Front 34

response order effects: visual

Back 34

primacy