FA1 Flashcards

1
Q

Correlational, ordinal (qualitative)

A

Spearman’s correlation coefficient

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2
Q

Correlation, interval or ratio (quantitative), non-parametric

A

Spearman’s correlation coefficient

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3
Q

Correlation, interval or ratio (quantitative), parametric

A

Pearson’s correlation coefficient

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4
Q

Experimental, independent groups, ordinal

A

Mann-Whitney u test

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5
Q

Experimental, independent groups, interval or ratio, non-parametric

A

Mann-Whitney u test

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6
Q

Experimental, independent groups, interval or ratio, parametric

A

T-test (unpaired)

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7
Q

Experimental, matched participants or repeated measures, ordinal

A

Wilcoxon-signed ranks test

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8
Q

Experimental, matched participants or repeated measures, interval or ratio, non-parametric

A

Wilcoxon-signed ranks test

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9
Q

Experimental, matched participants or repeated measures, interval or ratio, parametric

A

T-test (paired)

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10
Q

Design
* Independent groups design
* Sample Size: 20 participants

A

Mann-Whitney U
- Independent groups design
- Not normally distributed data as sample is less an 15/group

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11
Q

Why do you use mean as a central tendency?

A

Because there are no outliers

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12
Q

Why do you use median as a central tendency?

A

Because there are outliers

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13
Q

Where you are giving your “opinion/rating” =

A

Ordinal

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14
Q

Where you are stating a “measured” variable e.g. time =

A

At least interval

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15
Q

Note:
Independent groups design means

A

two names = Mann-Whitney

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16
Q

E.g. relationship question + answer

The relationship between age and the identification of faces in ambiguous pictures

A

The relationship is positive and strong

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17
Q

Contrasting current research and previous research

A

The Pearson correlation coefficient for the current research (0.98) is larger than the Pearson correlation coefficient for previous (0.70) indicating a stronger relationship

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18
Q

Conclusion =

A

As … (e.g. age) increases, so does the … (e.g. identification of faces in ambiguous figures) significantly increases

19
Q

Distinguish standard deviation e.g.

A

The data for the matching condition (1.17) had a larger standard deviation compared to the data for the mismatching condition (0.79).

20
Q

Greatest variability =

A

Largest standard deviation

21
Q

Strong

22
Q

Moderate

23
Q

Weak

24
Q

p = 0.05 or more

A

Fail to reject

25
p = <0.05
Reject
26
Independent groups design
Groups only try one condition, Mann-Whitney U
27
Repeated measures design
The groups try both conditions
28
Parametric for experimental
More than or equal to 15
29
Parametric for correlational
More than or equal to 25
30
Standard error of the mean
Precision of estimating the population mean (higher is less precision)
31
If the tail of graph is on the left it is
negative
32
If the tail of graph is on the right it is
positive
33
What does a distinguish question require?
- Definition of 1st concept - 'whereas' (conjunction) - Definition of 2nd concept
34
What does a contrast question require?
- Definition of 1st concept (what do they share) - 'whereas' (conjunction) - Definition of 2nd concept (where do they differ) (GIVE MORE)
35
What does a compare question require?
- State a similarity using concept 1 and 2 'are both' - State a difference using concept 1 'whereas' concept 2 - State a significance of either the similarity OR difference 'this is significant because...'
36
Confidence interval
range of values true population mean
37
The smaller the confidence interval...
the more precise the estimate and the greater the certainty when estimating the population mean
38
Less than .05 p-value
statistically significant and the null hypothesis can be rejected, the alternative hypothesis is supported
39
Equal to or greater than .05 p-value
not statistically significant and the null hypothesis cannot be rejected
40
Error bars are overlapping
no statistical significant difference
41
Error bars are not overlapping
there is a statistically significant difference between the two conditions
42
Error bars are substantially overlapping
no statistically significant difference
43
Type I error
P-value said there is a significant difference but in the population there is actually no significant difference Also known as a false positive
44
Type II error
P-value said there is no significant difference but in the population there is actually a significant difference Also known as a false negative