Correlation Flashcards

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1
Q

Two tailed correlation hypothesis

A

‘There will be a significant correlation between co-variables y and z’.
No direction given

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2
Q

One tailed correlation hypothesis

A

‘There will be a significant positive/negative correlation between co-variables y and z’

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3
Q

Null hypothesis

A

Can be retained if the alternative hypothesis is not supported by the evidence.
‘There will not be a significant correlation between co-variables y and z; any relationship will be due to chance factors’.

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4
Q

Primary data

A

Data gathered directly from the participants by the researcher.

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5
Q

Secondary data

A

Data that has already been gathered by someone other than the researcher.

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6
Q

Difference between findings and conclusions.

A

Findings: raw data e.g. mode, median, mean, range, outliers).

Conclusions: broad inferences that you can make from that raw data e.g.direction of correlation (positive/negative/no correlation), strength of correlation.

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7
Q

Inferential statistics for correlation

A

Positive correlation: a correlation that has a plus sign as part of its correlation co-efficient (e.g. +0.58).

Negative correlation: a correlation that has a minus sign as part of its correlation co-efficient (e.g. -0.72)

No correlation: a correlation with a co-efficient around 0 (e.g. +0.12 or -0.17)

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8
Q

Correlation study in practice

A
  1. Each participant in psychology class tested their reaction speed by tapping on their screen once a green light turns red.
  2. Then each participant was asked to rate their tiredness on the Stanford Sleepiness Scale.
  3. No correlation was found between the co-variables so they had no relationship.
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9
Q

Disadvantages of correlation studies.

A
  • They don’t tell us anything about cause and effect (e.g. if it was established there was a positive correlation between amount of violent TV people watched and level of aggression, this wouldn’t tell us what is causing what).
  • The inferential statistical tests won’t always pick up on a relationship between two co-variables (e.g. a curvilinear relationship would produce a correlation co-efficient of 0 even though there’s a pattern to the relationship.
  • Because correlation studies involve investigation of the statistical relationship between two co-variables, they don’t require the collection of any qualitative data which limits our ability to know what sits behind any relationship that might be found.
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10
Q

Experiments vs correlations

A
  • Experiments are looking to see cause and effect of the IV on the DV.
  • Experiments study the difference between IV’s influence on the DV.
  • Correlations are examining how 2 unmanipulated co-variables have an effect on eachother.
  • Correlations study the relationship between two co-variables.
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