correlations

Question 1

what does a correlation illustrate

Answer 1

strength and direction of an association between 2 or more co-variables

Question 2

what are co-variables

Answer 2

• variables investigated within a correlation (eg. height/weight)
• not referred to as IV or DVs as correlation investigates association between variables rather than the cause-effect relationship

Question 3

where are they plotted

Answer 3

scattergrams - once co-variable on x-axis and one on y-axis

Question 4

what are the three types of correlation

Answer 4

• positive correlation
• negative correlation
• zero correlation

Question 5

define a positive correlation

Answer 5

as one co-variable increases, so does the other

Question 6

define a negative correlation

Answer 6

as one co-variable increases, the other decreases

Question 7

define zero correlation

Answer 7

no relationship between co-variables

Question 8

difference between correlations and experiments

Answer 8

• experiment = researcher controls/manipulates IV and measures effect on DV
• correlation = no manipulation of one variable and thus, not possible to establish cause/effect between 1 co-variable & another

Question 9

strengths of correlations - useful preliminary tool for research (1)

Answer 9

P: useful preliminary tool for researcy
E: by assessing strength/direction of a relationship, they provide precise & quantifiable measure of how 2 variables are related - may suggest ideas for future research if variables strongly related/interesting pattern
—-> often used as starting point to assess possible ptterns between variables prior to researchers committing to a study

Question 10

strengths of correlations - quick & economical (2)

Answer 10

P: relatively quick & economical to carry out
E: no need for controlled environment & no manipulation of variables - secondary data can be used which means they’re less time-consuming

Question 11

limitations of correlations - tell us how variables are related not why (1)

Answer 11

P: tell us why variables are related and now why
E: cannot demonstrate cause/effect and thus, we do not know which co-variable is causing the other to change —> establishing direction of effect is an issue

Question 12

limitations of correlations - untested variables (2)

Answer 12

P: possible that untested variables are causing the relationship = intervening variable
eg. high pressuring jobs can cause anxiety and these people also drink a lot of caffeine as they work long hours - intervening variable is job type

Question 13

limitations of correlations - misused/misinterpreted (3)

Answer 13

P: correlations occasionally misused/misinterpreted
E: relationships between variables sometimes presented as casual when they’re not - esp. by media