correlations Flashcards
1
Q
what is a correlation?
A
a mathematical technique in which a researcher investigates an association between two variables, called co-variables
2
Q
what are co-variables?
A
- the variables investigated within a correlation eg. height and weight
- they are not referred to as the independent and dependent variables because a correlation investigates the association between the variables rather than trying to show a cause-and-effect relationship
3
Q
where and how are correlations plotted?
A
- on a scattergram
- one co-variables is represented on the x-axis and the other on the y-axis
- each point on the graph is the x and y position of each co-variable
4
Q
what is a positive correlation?
A
- as one co-variable increases so does the other
- eg. the number of people in a room and noise tend to be positively correlated
5
Q
what is a negative correlation?
A
- as one co-variable increases the other decreases
- eg. the number of people in a room and amount of personal space tend to be negatively correlated
6
Q
what is a zero correlation?
A
- when there is no relationship between the co-variables
- eg. association between number of people in a room in manchester and total daily rainfall in peru is likely to be zero
7
Q
what is the difference between correlations and experiments?
A
- in an experiment, the researcher manipulates the IV to measure the effect on the DV
- this deliberate change in one variable makes it possible to infer that the IV caused any observed changes in the DV
- however, in a correlation, there is no manipulation of one variable so it is not possible to establish cause and effect between one co-variable and the other
- even if we found a strong positive correlation between two co-variables, we cannot assume that one caused the other
8
Q
what are curvilinear relationships?
A
- some relationships are more complicated than positive or negative correlations
- the yerkes-dodson law of arousal states that performance is at its best when there is a moderate (optimal) level of arousal and will deteriorate if the arousal level is too low or too high
9
Q
evaluation: useful preliminary tool for research
A
- by assessing the strength and direction of a relationship, they provide a precise and quantifiable measure of how two variables are related
- this may suggest ideas for possible future research if variables are strongly related or demonstrate an interesting pattern
- therefore, correlations are often used as a starting point to assess possible patterns between variables before researchers commit to an experimental study
10
Q
evaluation: relatively quick and economical to carry out
A
- no need for a controlled environment and no manipulation of variables is required
- data collected by others (secondary data eg. government statistics) can be used, which means correlations are less time-consuming than experiments
11
Q
evaluation: correlations can only tell us how variables are related but not why
A
- due to the lack of experimental manipulation and control within a correlation
- cannot demonstrate cause and effect between variables so we don’t which which co-variable is causing the other to change
- therefore, establishing the direction of the effect is an issue
12
Q
evaluation: intervening variables
A
- it may be the case that another untested variable is causing the relationship between the two co-variables we are interested in
- this is called an intervening variable, also known as the third variable problem
13
Q
evaluation: occasionally misused or misinterpreted
A
- largely because issues such as intervening variables and knowing how but not why, correlations can occasionally be misused or misinterpreted
- relationships between variables are sometimes presented as causal when they aren’t
- eg. in the claim that people from ‘broken’ homes become criminals, an intervening variable, such as poverty being a cause of a broken home and also the key factor in criminality, might explain the apparent link
