Repeated Measures Design and Correlations Flashcards

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1
Q

What is a repeated measures design?

A

Participants are tested in 2 conditions (or more)

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2
Q

What are the advantages of repeated measures designs?

A

> Fewer participants are needed to run an experiment as compared to a between-groups design
This can save material, money and effort
Less error in your experiment than there would be if you had 2 separate groups

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3
Q

Disadvantage of repeated measures designs?

A

Practice/ Order effects

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4
Q

what factors can practice effects occur due to?

A

A number of different factors e.g. learning, fatigue, adaptation, habituation, sensitisation, contrast etc.

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5
Q

How do we combat practice/order effects?

A

COUNTERBALANCING

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6
Q

What is counterbalancing?

A

This means assigning participants to different conditions in different orders.

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7
Q

What is complete counterbalancing?

A

Takes into account every possible combination e.g. 123, 231, 312.

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8
Q

when does complete counterbalancing become more difficult?

A

when you have lots of different conditions- lots of different combinations.

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9
Q

What is partial counterbalancing?

A

randomly aelecting a sub set of possible conditions orders and assigning participants randomly to those.

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10
Q

One type of ______ design is called a correlational design.

A

Repeated measures

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11
Q

How many variables will a correlational design have?

A

2

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12
Q

What scales can variables be on in a correlational design?

A

either ordinal, interval or ratio.

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13
Q

What study design is this?

Increasing self harm is associated with lower self esteem.

A

Correlational design

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14
Q

A correlation is a description about how…

A

2 variable are associated with one another

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15
Q

name the 2 types of correlation.

A

Positive and Negative.

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16
Q

name this correlation type:

As one variable increases so does the other.

A

Positive :)

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17
Q

name this correlation type:

As one variable increases, the other decreases.

A

negative.

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18
Q

What is the descriptive statistic for a correlation?

A

A scatterplot :)

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19
Q

If you have an IV and a DV, what axis should the IV be on in a scatter plot?

A

The x-axis.

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20
Q

what can we draw to help us see a potentially significant trend on the scatter plot?

A

A line of best fit

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21
Q

What can the line of best fit show us?

A

A potentially sig relationship between 2 variables.

Also helps identifying outliers.

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22
Q

If correlation = 0 what does this mean?

A

There’s no correlation.

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23
Q

If correlation = -1 what does this mean?

A

Strong negative correlation

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24
Q

If correlation = +1 what does this mean?

A

Strong positive correlation

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25
Q

the stronger the correlation, the ____ the dots to the line of best fit.

A

closer

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26
Q

what does r stand for?

A

correlation :)

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27
Q

what is the strongest correlation you can get?

A

r= 1
OR
r = -1

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28
Q

What does r = 0 mean?

A

No linear relationship

29
Q

If there is no linear relationship what should we consider?

A

There might still be a non-linear relationship e.g. increase then decrease.

30
Q

What is an outlier?

A

A really unusual score

31
Q

There are 2 options re- what we do with our outliers?

A

delete it

OR

keep it and report the fact there is outliers.

32
Q

It’s probably best to do what with outliers?

A

delete them

33
Q

You can use a scatterplot to identify outliers, but what else could you use?

A

SPSS

34
Q

How do we identify outliers on SPSS?

A

If they are greater than or less than 3.29.

35
Q

Any significant correlation has a number of interpretations- what are these?

A
  1. We made a type I error
  2. Changes in A caused change in variable B
  3. Changes in B caused change in variable A
  4. Both changes in variables A and B influence each other
  5. the 3rd variable problem- and omitted variable C accounts for the link between A and B!
36
Q

Remember correlation is not ________.

A

causation

37
Q

don’t say A causes B- what should we say instead?

A

There’s a sig. relationship between A and B

38
Q

What visually represents our correlation?

A

scatterplot

39
Q

what is the coefficient determination?

A

literally jus the correlation multiplied by itself e.g. r squared.

40
Q

Caleculate the effect size:

r= .5

A

r squared = .25

41
Q

What does an effect size of .25 tell us?

A

25% of the variation in A can be accounted for by variation in B (or vice- versa).

42
Q

The left over percentage from the effect size .25 means what?

A

means that 75% of variation is due to random error and other things we haven’t measured.

43
Q

If effect size = 1 we could perfectly predict the ……

we couldn’t predict it at all of effect size was ___.

A

second variable

0

44
Q

what is a small effect size?

A

r2 = .01 to .08

45
Q

what is a medium effect size?

A

r2 = .09 to .24

46
Q

what is a large effect?

A

r2= .25 and above.

47
Q

What do parametric tests assume about your data?

A

> interval or ratio data
normally distributed- not skewed.
at least 10 participants on each level of you dependent variable.

48
Q

What is the parametric test for correlations?

A

Pearson Correlation Coefficient

aka. Pearsons

49
Q

What is the non-parametric test for correlations?

A

Spearman Rank Order Correlation

aka. Spearman’s Rho

50
Q

What is a one tailed hypothesis?

A

It states the direction of the correlation i.e. “there will be a significant positive correlation between…”

51
Q

What is a 2 tailed hypothesis?

A

It doesn’t give a direction- it just says “there is a significant correlation between the 2 variables”

52
Q

Pearson’s correlation revealed a significant, ______ correlation between self esteem and depression, r = -.88, n=54, p=.020.

What is the effect size?

A

negative

effect size = r2= .77

53
Q

The alternative hypothesis takes 2 different forms, what are they?

A

1 tailed and 2 tailed.

54
Q

in a 2 tailed hypothesis, what happens to the 5%?

A

It’s split 2.5% either side.

55
Q

In a 1 tailed hypothesis, what happens to the 5%?

A

The 5% is all to the one side.

56
Q

What is good about a 1 tailed?

A

Greater chance of accepting something as significant IF it’s in the direction you accepted.

57
Q

what data does Spearman’s Rho require?

A

at least ordinal

58
Q

Rs stands for….

A

Spearman’s Rho

59
Q

R s = .94, n=10, p=

A

NOTHING- no effect size reported in Sperman’s Rho.

60
Q

What are the 2 ways to report p values?

A

p = .xxx
OR
P < .001

61
Q

How many dp is p reported to?

A

3!

62
Q

Correlation can be used to establish ____ reliability.

A

test

63
Q

What is this called?:
Do same test to same sample of participants at 2 different times e.g. 1 week apart. Then correlate their scores on two sets of responses, if it’s a reliable measure then the 2 sets of scores should be highly correlated (>.70). Reported using standard format as a normal correlation (no need for effect size).

A

Test reliability

64
Q

What is split half reliability?

A

Add up scores from half test items.
Add up other half.
Both scores are then correlated, if both halves are measuring the same construct they should be highly correlated (> 0.70). rsb = .78 is how it’s reported.

65
Q

What is internal reliability also known as?

A

Cronbach’s alpha

66
Q

____ _____ represents the average degree to which each item is correlated with all other items.

A

Cronbach’s Alpha

67
Q

What should Cronbach’s alpha be above to indicate a reliable scale?

A

.70

68
Q

What does Cronbach’s alpha test?

A

Basically of all items on the scale are measuring the same thing.