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Psychology 3rd Year > Between Group Designs > Flashcards

Between Group Designs Flashcards

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1
Q

What do you need to have for between group designs?

A

2 separate groups!

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2
Q

In a between groups design, each participant only takes part in….

A

1 level of your IV

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3
Q

What is the difference between repeated measures and between group designs?

A

Between groups design- participants only take part in 1 level of IV

Repeated measures design- participants take part in all levels of IV

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4
Q

How should participants be assigned to a variable?

A

Randomly!

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5
Q

What is the purpose of random assignment to the groups?

A

Aim to evenly distribute random error.

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6
Q

Why is random assignment so important?

A

We don’t want systematic differences between our groups.

The maths assumes random error is spread equally across the 2 groups.

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7
Q

If you have parametric data and 2 separate groups- what statistical test are you going to use?

A

Independent t-test

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8
Q

The independent t test uses the t distribution to calculate the _____ of an observed event occurring.

A

Probability.

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9
Q

What’s important to consider about the scores of your groups?

A

To what extent they vary from each other.

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10
Q

If you have a low variability in group scores- what does this mean?

A

People have similar scores, aren’t varying as much, small SD.
Tiny bit of overlap between groups.

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11
Q

If you have medium variability in group scores- what does this mean?

A

scores are spread more, increase in SD, more variation.

More overlap.

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12
Q

Variation spreads even more. Huge degree of overlap between the 2 groups meaning there is less likely to be a significant difference between them.
What variability is this?

A

High!!

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13
Q

How would you calculate the t value?

A

t = difference in means/ variability in means

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14
Q

As the difference between ___________________ increases, the t value increases and is more likely to be significant.

A

2 means

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15
Q

As variability in means ____ the t value decreases and is less likely to be significant.

A

increases

aka. we want low variability for significant result!

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16
Q

A ____ t value is more likely to be significant.

A

larger

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17
Q

What hypothesis is this?

There is no difference between the means of your two groups.

A

Null Hypothesis

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18
Q

What hypothesis is this?

There is a significant difference between the means of your two groups.

A

Alternative Hypothesis

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19
Q

What hypothesis can take 2 different forms?

A

AH
1 tailed - states direction
and 2 tailed- doesn’t state a particular direction.

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20
Q

95% CI for girls’ scores = 2.44, 3.84.

What does this mean?

A

95% of the time the girls’ scores will be within this range.

21
Q

If the CIs for the 2 groups overlap what can we infer?

A

That results aren’t going to be significant!

22
Q

If the CIs for the 2 groups DONT overlap what can we infer?

A

That there is a difference between the groups and it’s likely to be significant.

23
Q

How do we write the t test results?

A

t (df) = t value, p = .xxx (one/two tailed) (effect size of sig)

24
Q

What test assesses homogeneity of variance? (e.g. do the 2 groups have similar levels of variation?)

A

Levene’s Test of Equality of Variances :)

25
Q

What are we hoping for the Levene’s Test of Equality of Variances?

A

That it’s a non-significant result!

e.g. > .05

26
Q

What is a small effect size (cohen)?

A

0.1

27
Q

What is a medium effect size (cohen)?

A

0.3

28
Q

What is a large effect size (cohen)?

A

0.5

29
Q

How do we calculate r (the effect size)?

A

√t2/ (t2 + df)

30
Q

Once you have conducted the independent t-test what do you need to remember to check for?

A

Homogeneity of variance!

using Levene’s Test.

31
Q

For parametric data what scale does your data have to be on?

A

Interval/Ratio

32
Q

For parametric data how many participants do you need in each group?

A

at least 10 people in each group!

33
Q

What is alpha and power set at?

A

alpha 0.05

power 0.80

34
Q

If you have a between groups design BUT data isn’t parametric e.g. ordinal data, skewed, what test do you use?

A

Mann-Whitney U

35
Q

What is the non parametric version of the independent t-test?

A

Mann- Whitney U

36
Q

What is the sign for Mann-Whitney U?

A

U :)

37
Q

If it’s a one tailed test what do you have to do to the p?

A

divide it by 2!

38
Q

Parametric tests are more statistically powerful than non-parametric tests this means you need ____ people to carry out a parametric test.

A

LESS

39
Q

If we have more than 3 independent groups and non-parametric data what test do we use?

A

Kruskall Wallis

40
Q

What test is an extension of the mann-whitney U for 3 groups?

A

Kruskall Wallis Test

41
Q

What do the Mann- Whitney U and Kruskall Wallis involve?

A

Ranking the data :)

42
Q

What is the sign for Kruskall Wallis?

A

H

43
Q

What test would you get a result like this from?

H(2) = 11.4, p= .003

A

Kruskall Wallis

44
Q

After the Kruskall Wallis what do we have to do?

A

Follow up tests!

45
Q

What follow up tests do we use for a Kruskall- Wallis?

A

Follow up Mann-Whitney U tests.

46
Q

What do we need to remember when conducting follow up Mann - Whitney U tests?

A

Do Bonferroni Correction!

47
Q

What would the Bonferroni Correction be if we had 3 follow up tests?

A

.05/3 = .017

48
Q

we can add an effect size to a t-test but not to a ….

A

Mann-Whitney U test

49
Q

How do you report the Mann-Whitney U test?

A

U = mann whitney u, p = .xxx (one-tailed)

Psychology 3rd Year (13 decks)

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