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PSYC210 > Principles of Psychological Research > Flashcards

Principles of Psychological Research Flashcards

1
Q

rules

A

principles of good design to set up for data collection

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2
Q

tools

A

summarising and describing data you’ve collected

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3
Q

theory

A

math behind rules and tools (stats)

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4
Q

psychology

A

scientific study of behaviour and mental processes

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5
Q

aristotle and plato

A

nature and origin of knowledge and thought

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6
Q

locke, hume, descarte and kant

A

philosophers question mind in 17th-19th century

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7
Q

wilhelm wundt (1879)

A

psychology became a science and studied structuralism

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8
Q

structuralism

A

mental events can be broken into components

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9
Q

william james (1890)

A

psychology is the science of mental life

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10
Q

4 goals of science

A

description, explanation, prediction and control

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11
Q

authority approach

A

seeking knowledge from sources thought to be valid and reliable

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12
Q

analogy approach

A

analogy between some event and a more familiar event

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13
Q

rule approach

A

try to establish laws or rules that cover a variety of different observation

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14
Q

empirical approach

A

testing ideas against actual events

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15
Q

hypothesis

A

an idea or tentative guess

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16
Q

population

A

members of a specific group

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17
Q

descriptive statistics

A

summarise the data collected from the sample

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18
Q

inferential statistics

A

generalise from the sample to the population

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19
Q

dependent variable

A

measurement taken

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20
Q

operational definition

A

specification of how the property of interest will be measured

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21
Q

validity

A

a DV is valid if it measures what it’s suppose to

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22
Q

reliability

A

DV is reliable if under the same conditions it gives the same measurement

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23
Q

bias

A

DV is bias when consistently inaccurate in one direction

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24
Q

ceiling effect

A

too easy task causes all scores to be too high

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25
Q

floor effect

A

too difficult task causes all score to be low

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26
Q

nominal scale

A

categorises without ordering (1-women, 2-man)

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27
Q

ordinal scale

A

categorises and orders categories (1-highlanders, 2-blues)

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28
Q

interval scale

A

categorises, orders and establishes an equal unit of measurement (celsius)

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29
Q

ratio scale

A

categorises, orders, establishes an equal unit of measurement and contains a true zero point (no. of items recalled in memory task)

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30
Q

independent variables

A

experimental factors that distinguish your group manipulated by the experimenter

31
Q

levels

A

specific conditions of the IV

32
Q

manipulated variable

A

factor directly manipulated by the experimenter

33
Q

subject variable

A

factor not directly manipulated. what the experimenter can’t assign

34
Q

true experiment

A

manipulated IV so can create a prediction and explanation as involves random assignment

35
Q

quassi experiment

A

subject variable so only creates a prediction and can’t state causation

36
Q

Woolfolk, Castellan and Brooks

A

Pepsi challenge was confounded by people prefering the letter ‘S’ to ‘L’

37
Q

control group

A

comparison group, differs from the experimental group from a lack of treatment

38
Q

placebo

A

thinking you’re receiving the treatment altering the results

39
Q

single blind design

A

participants not knowing which treatment group they’re in

40
Q

double blind design

A

neither experimenter or participants know the treatment group

41
Q

demand characteristics

A

cues in a situation that people interpret as demands for a particular behaviour

42
Q

between subjects design

A

each participant is tested in only one level of the IV which is easy to confound

43
Q

within subjects design

A

subject tested in each treatment where it is easier to detect systematic differences

44
Q

order effects

A

the order in which participants experience levels can be a problem (practise effects)

45
Q

counterbalancing

A

each treatment condition is equally exposed to practise effects and demand characteristics in the within subjects design.

46
Q

control variables

A

any extraneous variables that are held constant

47
Q

multiple independent variables

A

sees interaction between IVs and with DV. The relationship between one IV and the DV may change as the levels of other IV(s) change

48
Q

factorial design

A

when there are multiple IVs and you collect data in all combinations of the levels of your IVs (crossed)

49
Q

mixed design

A

one IV within and one IV between where each participant receives one

50
Q

main effects

A

the effects of one IV on the DV ignoring other IVs (one for each IV)

51
Q

interaction effects

A

effects of one IV on the DV taking into account other IVs, interaction for every combination of IVs

52
Q

frequency distribution

A

lets us see how values are distributed

53
Q

inferential statistics (variability)

A

variability affects the kinds of statements we can make and how certain we are about those statements

54
Q

descriptive statistics (variability)

A

how we describe the data so variability allows us to model the data

55
Q

range

A

largest score minus the smallest score

56
Q

mean deviation

A

all the data points minus the mean over n - always ends up being 0

57
Q

variance

A

all the data points minus the mean squared over number of participants

58
Q

standard deviation

A

approximately the average distance of the scores in a data set

59
Q

unbiased sd

A

sd equation but minus one off the number in sample

60
Q

inflection point

A

point where the curve begins to bend outward more (at each standard deviation point

61
Q

within 1 sd

A

68% of data

62
Q

within 2 sd

A

96% of data

63
Q

within 3 sd

A

99.7% of data

64
Q

z scores

A

tells us how far a score is from the mean which is measured in standard deviations

65
Q

z score formula

A

z = data point minus the mean over the standard devation

66
Q

z distribution

A

standardised normal distribution to compare things easily where mean = 0 and sd=1

67
Q

correlation

A

if two or more DVs are related which can be used to describe and predict behaviour and direct research

68
Q

bower (1990)

A

correlation between likeliness of low birthweight and premature birth with stress of mother during pregnancy

69
Q

Perason’s r

A

computes a correlation numerically from -1 to 1

70
Q

Pearson’s r assumptions

A

only detects linear relationships, have to be measured on the same individuals, must be measured on ratio or interval scale

71
Q

curvilinear

A

negative parabola shape (yerkes-dodson curve)

72
Q

cross lagged panel correlation

A

assumes that if X causes Y it will be stronger over timer

73
Q

directionality problem

A

Y caused X or X caused Y?

PSYC210 (2 decks)

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