Correlations

• Correlations

  • Shows how things are linked together
  • Indicates strength and direction of the relationship between co-variables
• Co-variables

  • Correlations are quantitative so co- variables are reduced to numbers
• Scatter diagrams

  • Correlations are plotted on a scatter graph
  • Shows direction and strength of correlation
  • one co-variable goes on x axis and the other on y axis
• Positive correlation

  • Two co-variables INCREASING/ DECREASING
  • As one co-variable increases the other co-variable increases
• Negative correlation

  • As one co-variable increases, the other decreases OR
  • as one co-variable decreases, the other increases
• Zero Correlation

  • No relationship between co-variables
• Strong correlation

  • Close points together on a line
• Weak correlation

  • Further apart the points are on the line
• STRENGHTHS of correlations

  • Allow naturally occurring variables to be investigated- no manipulation done
  • This means they can be used when other research methods can't because of ethical issues- may be unethical to test experimentally
  • Useful starting point for research- researcher can see if co-variables are connected
  • This gives researcher ideas for future investigations to further investigate the relationship
  • Can be used to investigate complex relationships- curvilinear relationships between two variables. Many uses
• Weakness of correlations

  • Can't establish cause and effect relationships between two co-variables, don't know how they are related
  • A positive correlation may be used but correlations can't show that one causes the other directly- 3rd variable (intervening variables)
  • Intervening variables can affect co-variables because of the lack of control on extraneous variables so it is possible to draw a incorrect conclusion
  • Large amounts of info is needed for it to be useful- establishing relationships from small sample= not reliable
  • collecting large data set for reliability= time consuming