correlations

• Correlation

  • Illustrates the strength and direction of an association between 2 co-variables
  • Scattergram = one co-variable is on the x-axis, the other is on the y-axis
  • Types of correlation:
  • Positive correlation = co-variables increase together
  • Negative correlation = one co-variable increases, the other decreases
  • Zero correlation = no relationship between variables
  • In an experiment = the researcher manipulates the IV and records the effect on the DV
  • In a correlation = there is no manipulation of variables and so cause and effect cannot be demonstrated
• correlations evaluation

  • Strength = useful starting point for research
  • Correlations provide a measure of how 2 variables are related
  • If variables are strongly related, it may suggest hypotheses for future research
  • Strength = relatively economical
  • Unlike lab study, there is no need for a controlled environment and can use secondary data (eg government statistics)
  • => correlations are less time-consuming than experiments
  • Limitation = no cause and effect
  • Correlations are often wrongly presented as causal when they only show how 2 variables are related
  • Leads to false conclusions about causes of behaviour
  • limitation = intervening variables
  • Another untested variable may explain relationship between co-variables
  • May also lead to false conclusions