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Correlation

Correlation is a statistical technique which shows how closely linked two sets of scores are.

Correlations

Correlations

  • Correlation is a statistical technique which allows researchers to compare two sets of scores to see whether two variables are linked.
    • For example, they could compare scores on a school exam with the number of hours that students had spent studying.
Positive vs negative

Positive vs negative

  • A positive correlation is where the scores rise and fall together. As one variable rises, so does the other.
  • A negative correlation is where the scores rise and fall in opposite directions. As one variable rises, the other falls.
Zero correlation

Zero correlation

  • Sometimes, there is a zero correlation.
  • This is where there is simply no statistical link at all between the variables - the scores are not connected in any way.
Strength of correlation

Strength of correlation

  • Both positive and negative correlation can be weak or strong.
  • A strong correlation is where the scores rise and fall very closely, while a weak correlation suggests a much more distant relationship between the variables (for example a large rise in one might link to a very small rise in the other).
Correlation vs causation

Correlation vs causation

  • Researchers must be careful not to conclude that a strong correlation means that one variable is having an effect on the other.
  • This could be the case, but it can’t be concluded from the correlation alone - further evidence would be needed.

Correlation Coefficient and Evaluation

Correlation coefficients tell us about the strength of the relationship. A coefficient of +1 is a perfect positive correlation, -1 a perfect negative correlation and 0 no correlation.

Spearman’s Rho

Spearman’s Rho

  • Correlation coefficients are calculated using Spearman’s Rho, which measures how strong the association is between two variables.
  • Once a coefficient has been calculated, it is necessary to consult critical value tables to determine whether the result is statistically significant. Critical value tables state that calculated values must be greater than or equal to the critical value in order to be significant (reject the null hypothesis).
Confusions: Spearman's Rho

Confusions: Spearman's Rho

  • This can be confusing, if for example the calculated value of Spearman’s Rho was -0.78 and the critical value was 0.648, it might be assumed that -0.78 was less than the critical value.
  • However, when a correlation coefficient is calculated, the minus sign (-) does not have a numerical value, it simply denotes the correlation is negative.
  • In this example, the calculated result is significant and denotes a strong negative correlation.
Evaluation of correlational research

Evaluation of correlational research

  • Advantages
    • They measure the strength of a relationship.
    • They are a 1st step in research.
  • Disadvantages
    • They cannot show cause, only a relationship.
    • They do not reflect curvilinear relationships.
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