Week 10 Flashcards

1
Q

correlation studies

A

no manipulation
no independent or dependent variables
measuring to see if 2 or more variables are related

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2
Q

scatterplots

A

help us determine if relationships are linear
if related we can draw a line through the points

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3
Q

curve lines

A

a nonlinear relationship
such a a inverted U relationship
e..g the relationship between arousal and memory

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4
Q

positive relationship

A

both variables increase

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5
Q

negative relationships

A

one variable increases, other variable decreases

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6
Q

correlation coefficient

A

shows strength and direction of relationships
range from +1 to -1
+/- is the direction
1 is the strength

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7
Q

closer to 0

A

weaker correlation
what counts as a strong correlation is context dependent

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8
Q

Pearsons r and Spearman’s rho

A

both make the assumption that the relationship is linear

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9
Q

Pearsons r

A

data is interval/ratio

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10
Q

Spearman’s rho

A

data is ordinal

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11
Q

Pearsons r is

A

how far from the mean each participant falls
quantifies how far participants deviate from the mean on one variable predicts deviation from mean on other variables

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12
Q

Spearman’s rho is

A

ranks participants independently on each variable
quantifies the extent to which rank one predicts the rank on other variables

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13
Q

postive coefficient

A

postive relationship

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14
Q

negative coefficient

A

negative relationship

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15
Q

correlation coefficient is

A

a descriptive statistic

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16
Q

null hypothesis

A

no correlation
p value quantifies how much our observed sample correction differs from what we’d expect if the null was true

17
Q

alternate hypothesis

A

can be one tailed or two tailed

18
Q

what shouldn’t we do?

A

draw casual conclusions

19
Q

what should we do?

A

consider how many correlations have been conducted
large datasets which lots of positive correlations produce spurious correlations

20
Q

spurious correlations

A

not meaningful and don’t reflect a true relationship

21
Q

random error

A

caused by unknown and unpredictable changes in the experiment
doesn’t effect the mean but changes the range of scores around the mean

22
Q

systematic error

A

reproducible and consistent in the same direction
effects the mean

23
Q

to reduce the error

A

repeat measurements
apply correction factors
pilot study
training the experimenter
training the participants
triangulation

24
Q

triangulation

A

suing more than one measure of a particular behaviour
a group of measurement tools won’t have the same error

25
validity
how accurate is our research measuring the desired behaviour
26
internal validity
effects observed are due to independent variable not other factors
27
ecological validity
external results can be generalised to other settings
28
population validity
external results can be generalised to other people
29
predictive validity
external whether our measure predicts other related behaviours
30
construct validity
external are we measuring what we think we are measuring
31
face validity
on 'face value' it seems the measure is appropriate
32
reliability
consistency of our measure or results
33
internal reliability
applies only to questionnaires do items thats purpose is to measure the same thing have consistent responses
34
external reliability
extent a measure varies from one use to another
35
test retest
same person fills out the same results it should be the same
36
random error in a questionnaire
natural small variations over time
37
systematic error in a questionnaire
social desirable responding