Chapters 6,7 Flashcards

1
Q

experimentors

A

investigations where researcher manipulates an independent variable

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2
Q

nuance for experimements

A

groups of participants must be equal

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3
Q

correlational studies

A

an investigation that explores the effect of a subject variable on a dependent variable

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4
Q

how to make it experimental

A

randomly assign participants into groups, placebo control

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5
Q

between groups experiment

A

both groups are very similar and are treated equally

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6
Q

control group

A

exposed to the same conditions as the experimental group, except for the manipulation of the independent variable

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7
Q

experimental group

A

exposed to the specific treatment or manipulation of the independent variable being investigated

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8
Q

equivalent groups

A

control and experimental groups must be equal

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9
Q

selection bias

A

the confound arising when there are differences between the comparison groups in a study

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10
Q

matching

A

identifying alike participants then randomly assigning them to different groups

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11
Q

pretesting

A

identify similar characteristics prior to matching

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12
Q

ceiling effect

A

a measure yields scores near the top limit of measurement for one or all groups

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13
Q

floor effect

A

dependent variable measurements yields scores near the lower limit

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14
Q

within-subjects design

A

an investigation where every participant receives every level of the independent variable at least once

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15
Q

pretest-posttest

A

one group of participants is tested twice using the same measurement tool, once before and once after the independent variable is manipulated

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16
Q

repeated-measures design

A

involved multiple measurements per participant

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17
Q

longitudinal design

A

within-subjects design where participants are tested multiple times except it looks for changes over a long period of time

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18
Q

advantages of within-subjects design

A

often requires fewer participants, takes less time, subject variables remain constant across the experimental conditions, error variance is reduced

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19
Q

why fewer participants?

A

because participants perform in each of the experimental conditions

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20
Q

lower error variance

A

less error variance = more powerful test of the IV’s effect

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21
Q

type 1 error

A

occurs when you incorrectly reject a true null hypothesis

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22
Q

type 2 error

A

occurs when you fail to reject a false null hypothesis

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23
Q

extraneous variable

A

anything that could influence the dependent variable

24
Q

confounding variable

A

influences the dependent variable and also correlates with or causally affects the independent variable

25
Q

operational definition

A

clear and specific description of how a variable will be measured, observed, or manipulated in a research study

26
Q

reliability

A

the consistency with which the same results are obtained from the same test, instrument, or procedure

27
Q

validity

A

the extent to which a measurement actually measures what it is supposed to

28
Q

internal validity

A

the extent to which the design of an experiment ensures that the IV caused the change in DV

29
Q

external validity

A

the generalizability of the study

30
Q

population

A

all the organisms to which the researcher wishes to generalize their research results

31
Q

sample

A

a subset of the population, a sample of the population used in the study

32
Q

random sampling

A

randomly selecting participants from the population to be part of your sample

33
Q

convenience sampling

A

participants are not randomly chosen, they just happen to be in the right place at the right time

34
Q

hypotheses vs. prediction

A

hypothesis is more general than a prediction, prediction is derived from the hypothesis

35
Q

null hypothesis

A

the prediction that nothing is different, there is no difference between groups

36
Q

alternative hypothesis

A

the hypothesis upon which the researchers prediction is made- there is a difference in the groups

37
Q

two-tailed hypothesis

A

researcher does not predict a specific direction of the difference between groups

38
Q

one-tailed alternative hypothesis

A

researcher predicts the direction of the difference between groups

39
Q

region of rejection

A

a special zone that helps researchers decide whether their data provides strong evidence to support a new idea or hypothesis

40
Q

cons of within-subjects

A

demand characteristics, carryover effects, unrelated event impact

41
Q

demand characteristics

A

when a participant derives information about what is expected

42
Q

carryover effects

A

having a participant repeat some measure multiple times

43
Q

history effect

A

the result of an event that occurs outside the experiment at the same time the independent variable is being changed

44
Q

maturation effect

A

a change in performance due simply to the passage of time

45
Q

regression towards the mean

A

people who scored really high or low tend to score closer to the mean the next time they take the test

46
Q

counterbalancing

A

presenting experimental conditions to participants in different orders so that carryover effects are controlled

47
Q

ABBA counterbalancing

A

participants get all conditions

48
Q

block randomization

A

used when you have 3 or more conditions

49
Q

random order with rotation

A

the experimental conditions are ordered randomly and the first participant receives this order and its changed for every participant

50
Q

downside of matching participants

A

can be hard to find matching criteria for every participants, resource and time intensive, loss of generalizability

51
Q

resource and time intensive

A

may require additional data collection, data cleaning, and careful consideration of matching variables

52
Q

loss of generalizability

A

you could end up with groups that are so homogenous that they no longer represent the broader population accurately

53
Q

cross-sectional study

A

data is collected from different groups of participants at a single point in time with the aim of comparing differences between these groups

54
Q

pros of cross-sectional study

A

efficient, no participant drop out, good for population trends

55
Q

cons of cross-sectional study

A

does not generate causal results, can’t track the changes over time, susceptible to cohort effects

56
Q

temporal priority

A

the independent variable must come before the dependent variable is measured

57
Q

control extraneous variables

A

there should be no confounds that could act as alternate explanations