Correlations

• A weakness of the method is that it can only identify linear relationships and not curvilinear.
• Correlational techniques are non-experimental methods used to measure how strong the relationship is between two (or more) variables.
• In an experiment, the effect of an independent variable upon the dependent variable is measured; however, in correlational studies the movement and direction of co-variables in response to each other is measured.
• There is no claim of a cause and effect relationship, although after a correlational study has been conducted, further research will often be conducted to determine if one variable is, in fact, affecting the other.
• There are different types of correlation: positive, negative, and zero.
• Positive correlation: As one variable increases, the other variable increases, for example - height and shoe size.
• Negative correlation: As one variable increases, the other variable decreases, for example - the GCSE grades of students and the amount of time they are absent from school.
• Zero correlation: Occurs when a correlational study finds no relationship between variables, for example - the amount of rainfall in Wales and the number of people who have read the Lord of the Rings trilogy.
• Correlation is the degree and direction of the correlation between the co-variables, one of which is indicated on the X-axis and the other on the Y-axis.
• There are limitations associated with using the correlational method.
• Correlational studies measure the strength of a relationship between two (or more) variables, providing valuable insight for future research.
• Correlational studies are an ideal place to begin preliminary research investigations.
• Correlations only identify linear relationships and not curvilinear.
• Correlational analysis can be used when a laboratory experiment would be unethical as the variables are not manipulated, merely correlated.
• It is not possible to establish a cause and effect relationship through correlating co-variables.
• Secondary data can also be used in correlational studies, alleviating the concern over informed consent as the information is already in the public domain, such as government reports.
• A correlation coefficient is used to measure the strength and nature (positive or negative) of the relationship between two co-variables.
• The correlation coefficient number represents the strength of the relationship and can range between -1.0 and +1.0.
• The nearer the number is to +1 or -1, the stronger the correlation.
• A perfect positive correlation has a correlation coefficient of +1 and for a perfect negative correlation it is -1.
• A scattergram (sometimes called a scattergraph) is a graph that shows the correlation between two sets of data (co-variables) by plotting points to represent each pair of scores.