methods: correlational research

Question 1

what is a correlation

Answer 1

• way of looking at relationships between two variables
  
  • asses the degree to which two co-variables are related
• can be positive or negative
• positive correlation: when high values of one variable = high values of the other
• negative correlation: when high values of one variable = low values of the other
• if there’s no correlation between two variables they are said to be uncorrelated

Question 2

what are correlations useful for?

Answer 2

• for making predictions
• if two variable are correlated, you can predict one from the other
• eg if someone’s good at maths, they may well be good at physics

Question 3

who produces the scores in correlations?

Answer 3

• same person produces the two scores
• both measures have numerical data

Question 4

what are three important features of a correlation design?

Answer 4

• there’s no IV or DV. there are two variables of equal importance eg shoe size and height
• the hypothesis will be about a relationship between two variables (not about a difference)
• hypothesis could be directional as it could predict a positive or negative correlation eg there’s an positive relationship between length of time in analysis and the benefit of therapy. or non-directional as it could just state there will be a relationship but not state + or -

Question 5

how are co-variables measured?

Answer 5

• directly by the researcher, or obtained via secondary data gathered from other sources

Question 6

what do co-variables include within bio psych?

Answer 6

• measuring number to genes a person shares (closeness of family relationship) and a behavioural characteristic (amount of aggression shown)
• by plotting scores of these two variables on a scatter diagram it’s possible to see if there’s a relationship that exists between them

Question 7

strengths of correlations

Answer 7

• provides a means of looking at relationships and determining whether the relationship is significant
• useful way of conducting preliminary analysis on data
• may stimulate further investigations if a significant relationship is found between the co variables. eg exp to then be able to establish a causal link

Question 8

weaknesses of correlations

Answer 8

• cannot show cause and effect relationship (causality) as there’s no IV that’s been deliberately manipulated
• if co variables are correlated one may be causing changes in the other but we don’t know the direction of possible effect eg research shows there’s a positive correlation between hrs spent playing violent vid games and aggressiveness. it might be that watching violent vid games is increasing aggressiveness, or it could be more aggressive people choose to watch violent games
• there may be intervening variables that can explain why the co-variables are linked