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Understanding the mind Quizzes & Lectures > Psychology Statistics > Flashcards

Psychology Statistics Flashcards

1
Q

How do we get a t-distribution?

A

By repeatedly taking two samples from the same population and then taking the mean difference between the two samples.

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2
Q

All other things being equal, when are we more likely to get a statistically significant difference between two conditions?

A

When we have a smaller standard deviation.

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3
Q

What is the fundamental idea underlying statistical tests that compare the results from two observed samples?

A

The tests compare the difference between the observed samples with a distribution that is based on a comparison of two random samples.

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4
Q

If we find no significant difference between two conditions what can we conclude?

A

There is no evidence that the two samples came from different populations.

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5
Q

If we set our significance level at .05 and a statistical test shows that p = .062, what should we say?

A

The result is non-significant.

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6
Q

What does the t-test NOT take into account?

A

The difference in medians between your samples.

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7
Q

What does the Levene’s test for equality of variances tell you?

A

Whether the homogeneity of variance assumption is violated.

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8
Q

When do you use a related samples t-test?

A

When each participant contributed data in two conditions.

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9
Q

You therefore design a study to investigate if there is a difference between student and staff satisfaction of the new common room. Which experimental design and statistical tests would you use?

A

Independent samples design and independent samples t-test

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10
Q

how do you report the results of the t-test.

A

t(degress of freedom) = the t statistic, p = p value

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11
Q

When do we make a Type I error?

A

We reject the null hypothesis when the null hypothesis is in fact true.

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12
Q

What does the MS-between in an independent samples ANOVA tell us?

A

How large the differences between conditions are.

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13
Q

Which test checks whether the sphericity assumption in a repeated measures ANOVA is violated?

A

Mauchly’s test

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14
Q

how do you report the results of an analysis of variance

A

An ANOVA showed that there were significant differences between the conditions: F(2, 27) = 4.47, p = .021

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15
Q

What is the dependent Variable

A

The data that your participants provide, the variable that you measure, e.g., reaction times, score on a test, ratings, number of errors, etc.

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16
Q

What is the independent variable

A

The variable that you manipulate, the conditions or groups that are compared, either by comparing different groups of participants or comparing different stimuli.

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17
Q

If an independent Variable is Between Participants. each Participant takes part in

A

only one level/condition

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18
Q

If an independent Variable is Between Participants. each Participant takes part in

A

in all conditions/levels.

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19
Q

Inferential tests (t-test, ANOVA) check

A

how likely it is that the results from the different conditions in your experiment came from the same population.

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20
Q

If Inferential tests (t-test, ANOVA) show it is unlikely participants came from the same population we can conclude

A

that the difference between conditions is due to your experimental manipulation (e.g., whether participants were male or female, whether they drank coffee or not, whether the stimulus was large or small).

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21
Q

If the difference between conditions is due to your experimental manipulation we can say

A

The difference is statistically significant; the independent variable had a significant effect

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22
Q

Normally, we say that a difference is significant if the chance that the results from the conditions came from the same population is

A

less than 5%,
that is p < .05.

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23
Q

If it is quite likely that the results from the conditions came from the same population this means

A

we cannot conclude that the independent variable had an effect; the difference between conditions is non-significant

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24
Q

what is the Null hypothesis (H0):

A

That there is no difference between your conditions; the conditions were sampled from the same population.

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25
Q

what is the Experimental hypothesis (H1):

A

That there is a difference between conditions; the conditions were sampled from different populations.

26
Q

For the below Hypothesis determine there type

Condition A is larger than condition B

There is a difference between conditions A and B

A

Condition A is larger than condition B - A directional or One Tailed Hypothesis

There is a difference between conditions A and B - a non-directional, two-tailed hypothesis

27
Q

Why is it generally better to use a two tailed hypothesis

A

Because we usually cannot completely rule out that the difference goes in either direction

28
Q

how can Statistical tests check whether H0 can be rejected

A

If p < .05 it can be, and we accept H1. If p > .05, H0 cannot be rejected.

29
Q

If p = .05, then there is a 5% chance that

A

that this is a false positive, that we conclude that the samples came from different populations even though they did not, that we incorrectly conclude that the conditions are different.

30
Q

what type of error occurs when we conclude that the samples came from different populations even though they did not, that we incorrectly conclude that the conditions are different.

A

This is a Type I error.

31
Q

What type of error occurs if p > .05, and it is possible that this is a false negative, that we do not reject H0 even though the samples came from different populations

A

This is a Type II error

32
Q

What type of tests are the inferential tests t-test, ANOVA.

A

These are parametric tests

33
Q

What do Parametric test Compare

A

They compare the difference between the means of your conditions with the variability within your conditions (error variability/noise variability).

34
Q

Provide an examples of when Parametric tests are likely to indicate a statistically significant result

A

1.The mean difference between your conditions is large

2.The variability within your conditions is small

3.You have a larger number of observations

35
Q

What Assumptions should be met to use Parametric tests

A

Your dependent variable should be a measurement or scale variable.

Your data should be normally distributed.

Tests for independent samples designs: Variability in the conditions should not differ (homogeneity of variance assumption).

ANOVA for repeated measures design: Variability in the difference between each pair of conditions should not differ (sphericity assumption).

36
Q

Homogeneity of variance assumption
applies to which design method and means?

A

Applies to :
Tests for independent samples designs.
Means:
Variability in the conditions should not differ.

37
Q

The sphericity assumption
applies to which design method and means?

A

Apples to :
ANOVA for repeated measures design
Means:
Variability in the difference between each pair of conditions should not differ

38
Q

Which test do you use?
For a Study with:

  1. Condition
A

One sample t test

39
Q

Which test do you use?
For a Study with:

  1. Conditions

Participants are independent

A

Independent t test

40
Q

Which test do you use?
For a Study with:

  1. Conditions

Participants are repeated

A

Repeated t test

41
Q

Which test do you use?
For a Study with:

  1. or more Conditions

Participants are independent

A

One-Way Independent Measures ANOVA

42
Q

Which test do you use?
For a Study with:

  1. or more Conditions

Participants are repeated

A

One-Way Repeated Measures ANOVA

43
Q

If SPSS shows a p-value of .000, then you should

A

say p < .001 (or p < .01 if you report all p-values in 2 decimals).

44
Q

What is required to Write up a t-Test

A

Report means and a measure of variability (standard deviation, variance, standard error). This can be done in the text or (if you have many conditions, in a table or graph).

Define variables

Say which test you used and what your design was.

Report t-value, df (degrees of freedom) in parentheses, p-value

If you find a statistical difference, make clear what the direction of the difference is (check means)

45
Q

if the results of the test are not significant what can you NOT do

A

you cannot say that there was a difference between conditions.

46
Q

When are ANOVAs used

A

For experiments where you have more than two conditions

47
Q

If your experiment has 2 conditions then ANOVA will show

A

The ANOVA shows the same results as a t-test.

48
Q

If the ANOVA results are significant, then you can conclude

A

conclude that there are differences between your conditions.

49
Q

What can ANOVA not show

A

which conditions differ.

50
Q

in an experiment with more than 2 conditions how can you check whether two specific conditions differ?

A

With pairwise analyses.

51
Q

What is A priori pairwise analyses

A

You decided in advance which conditions you will compare.

52
Q

what pairwise analyses procedure can you use for A priori pairwise analyses

A

you can use the Least Significant Difference (LSD) procedure, which is identical to the t-test

53
Q

when using the Least Significant Difference (LSD) procedure, why is it better to limit the number of comparisons

A

to keep the experiment-wise error rate low

54
Q

What is Post-hoc pairwise analyses

A

You decide after seeing the data which conditions you will compare

55
Q

What kind of Pairwise analyses can you use for Post-hoc Analyses

A

You can use the Bonferroni correction or Tukey HSD test.

56
Q

why use A priori pairwise analyses or Post-hoc pairwise analyses

A

ANOVA results can show that there is a difference between you conditions but does not tell you which conditions differ.

To check whether two specific conditions differ, you do pairwise analyses.

57
Q

In an ANOVA What do MSbetween or MSmodel relate to?

A

The mean square of your independent variable

58
Q

In an ANOVA What do the MSwithin or MSerror relate to ?

A

The mean square of your error variance

59
Q

In reporting an ANOVA, what are the two df’s?

A

the MSbetween or MSmodel which is associated with the mean square of your independent variable

and

The MSwithin or MSerror which is associated with the mean square of your error variance

60
Q

If the ANOVA is significant what do you report to check which conditions differed

A

The pairwise comparisons (a priori or post hoc)

61
Q

If the ANOVA is not significant what dont you need to report

A

you do not report pairwise comparisons (because the ANOVA showed no significant differences between conditions)

Understanding the mind Quizzes & Lectures (8 decks)

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