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PSYC210 > Principles of Psychological Research > Flashcards

Principles of Psychological Research Flashcards

(73 cards)

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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
floor effect
too difficult task causes all score to be low
26
nominal scale
categorises without ordering (1-women, 2-man)
27
ordinal scale
categorises and orders categories (1-highlanders, 2-blues)
28
interval scale
categorises, orders and establishes an equal unit of measurement (celsius)
29
ratio scale
categorises, orders, establishes an equal unit of measurement and contains a true zero point (no. of items recalled in memory task)
30
independent variables
experimental factors that distinguish your group manipulated by the experimenter
31
levels
specific conditions of the IV
32
manipulated variable
factor directly manipulated by the experimenter
33
subject variable
factor not directly manipulated. what the experimenter can't assign
34
true experiment
manipulated IV so can create a prediction and explanation as involves random assignment
35
quassi experiment
subject variable so only creates a prediction and can't state causation
36
Woolfolk, Castellan and Brooks
Pepsi challenge was confounded by people prefering the letter 'S' to 'L'
37
control group
comparison group, differs from the experimental group from a lack of treatment
38
placebo
thinking you're receiving the treatment altering the results
39
single blind design
participants not knowing which treatment group they're in
40
double blind design
neither experimenter or participants know the treatment group
41
demand characteristics
cues in a situation that people interpret as demands for a particular behaviour
42
between subjects design
each participant is tested in only one level of the IV which is easy to confound
43
within subjects design
subject tested in each treatment where it is easier to detect systematic differences
44
order effects
the order in which participants experience levels can be a problem (practise effects)
45
counterbalancing
each treatment condition is equally exposed to practise effects and demand characteristics in the within subjects design.
46
control variables
any extraneous variables that are held constant
47
multiple independent variables
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
factorial design
when there are multiple IVs and you collect data in all combinations of the levels of your IVs (crossed)
49
mixed design
one IV within and one IV between where each participant receives one
50
main effects
the effects of one IV on the DV ignoring other IVs (one for each IV)
51
interaction effects
effects of one IV on the DV taking into account other IVs, interaction for every combination of IVs
52
frequency distribution
lets us see how values are distributed
53
inferential statistics (variability)
variability affects the kinds of statements we can make and how certain we are about those statements
54
descriptive statistics (variability)
how we describe the data so variability allows us to model the data
55
range
largest score minus the smallest score
56
mean deviation
all the data points minus the mean over n - always ends up being 0
57
variance
all the data points minus the mean squared over number of participants
58
standard deviation
approximately the average distance of the scores in a data set
59
unbiased sd
sd equation but minus one off the number in sample
60
inflection point
point where the curve begins to bend outward more (at each standard deviation point
61
within 1 sd
68% of data
62
within 2 sd
96% of data
63
within 3 sd
99.7% of data
64
z scores
tells us how far a score is from the mean which is measured in standard deviations
65
z score formula
z = data point minus the mean over the standard devation
66
z distribution
standardised normal distribution to compare things easily where mean = 0 and sd=1
67
correlation
if two or more DVs are related which can be used to describe and predict behaviour and direct research
68
bower (1990)
correlation between likeliness of low birthweight and premature birth with stress of mother during pregnancy
69
Perason's r
computes a correlation numerically from -1 to 1
70
Pearson's r assumptions
only detects linear relationships, have to be measured on the same individuals, must be measured on ratio or interval scale
71
curvilinear
negative parabola shape (yerkes-dodson curve)
72
cross lagged panel correlation
assumes that if X causes Y it will be stronger over timer
73
directionality problem
Y caused X or X caused Y?

PSYC210 (2 decks)

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