correlations

Question 1

correlation analysis

Answer 1

looks for a relationship between two associated co-variables

allows us to establish the type of relationship between the variables: whether it is positive, negative or a zero relationship

Question 2

positive correlation

Answer 2

as one co-variable increases, the other increases

correlation coefficient between 0 and +1

eg no hours spent revising v test scores

Question 3

zero correlation

Answer 3

there is no relationship between the two co-variables

correlation coefficient of 0

eg amount of pets v test scores

Question 4

negative correlation

Answer 4

as one co-variable increases, the other decreases

correlation coefficient of 0 and -1

eg no hours of sleep v likelihood of a car crash

Question 5

scattergraphs

Answer 5

relationship between two co-variables can be expressed graphically on a scattergraph

distribution of data points on the graph indicates the direction and strength of the relationship between co-variables

Question 6

correlation coefficients

Answer 6

relationship between two co-variables can be expressed quantitatively as a correlation coefficient

this is a number between -1 and +1 which indicates the direction and strength of the relationship between co-variables.

Question 7

data sloping upwards from left to right

Answer 7

indicates a strong positive relationship between the co-variables

Question 8

data sloping downwards from left to right

Answer 8

indicates a strong negative relationship between the co-variables

Question 9

first strength of correlation analysis s

Answer 9

• shows the strength of the relationship between two co-variables
• expressed quantitatively with a correlation coefficient, proving a precise measure of how two variables are related
• correlation coefficient is a number between +1 and -1 which allows researchers to establish the direction and strength of the relationship between co-variables
• if the variables are strongly related, it may suggest hypotheses for future research

Question 10

2nd strength of correlation analysis p

Answer 10

• unlike laboratory experiments (conducted in an artificial setting), it allows researchers to investigate behaviour that would be unethical to study in controlled conditions as it would cause physical or psychological harm which participants have the right not to experience
• this is due to CA making use of naturally occuring variation in the IV which is not directly manipulated by the experimenter
• eg it would be unethical to cause participants stress to see its effect on illness, so we use naturally occuring incidents of stress to shows the positive correlation with illness

Question 11

1st limitation of correlation analysis c

Answer 11

unlike laboratory experiments (conducted in artificial settings with control over variables), a limitation is that correlation analysis is that it has a low level of control over confounding variables (which are any uncontrolled variables that could systematically affect the DV)

this is due to correlations often make use of the real world, naturally occuring variation in the IV and so do not have control over confounding variables

as a result, a third (unknown) variable could in fact be the cause of the observed relationship between two co-variables

Question 12

2nd limitation of correlation analysis r

Answer 12

unlike lab experiments (conducted in an artificial setting with control over variables), a limitation is that it’s difficult to establish cause and effect which is when it is impossible to establish a casual relationship between two variables, lowering the internal validity of research

this is because correlation analysis only shows the strength and direction of the relationship between two co-variables; doesn’t show which variable caused the other.

in some cases, the direction of causality may appear clear, this isn’t true in every case

eg may appear that long-term stress causes illness however, becoming ill may cause stress.