Correlational Methods Flashcards
Correlational methods
Correlation refers to the relationship between two or more variables. The variables measured are known as co-variables. Positive correlation; as one variable increases the other one also increases and as one variable decreases the other one also decreases (eg, height and weight). Negative correlation; as one variable increases the other one decreases (eg, age and memory). When there is no relationship between two variables, this is known as a zero correlation.
Correlation does not imply causation. Intervening variable; variable used to explain the relationship between two variables.
Difference between Experiments and Correlations
An experiment tests the effect that an independent variable has upon a dependent variable whereas a correlation looks for a relationship between two variables.
Experiments establish cause and effect - correlations identifies associations between variables.
Scatter-grams
A correlation can be expressed visually. This is done by drawing a scatter-gram - that is one that can plot the figures for one variable against the figures for the other on a graph. When you draw a scatter-gram it doesn’t matter which variable goes on the x-axis and which goes on the y-axis. Remember, in correlations we are always dealing with paired scores, so the values of the 2 variables taken together will be used to make the diagram. Decide which variable goes on each axis and then simply put a cross at the point where the 2 values coincide.
Correlation coefficient
Instead of drawing a scatter-gram a correlation can be expresses numerically as a coefficient, ranging from -1 go +1. The correlation coefficient (r) indicates the extent to which the pairs of numbers for these 2 variables lie on a straight line. Values over zero indicate a positive correlation, while values under zero indicate a negative correlation.
Strength of correlation
When asked to describe a correlation, the first thing to mention is its direction (+ or -), the next is its strength. This can be described with terms such as perfect, strong, moderate, weak or no correlation.
Perfect = +1 / -1
Strong = +0.9-0.7 / -0.9-0.7
Moderate = +0.6-0.4 / -0.6/0.4
Weak = +-0.3-0.1 / -0.3-0.1
Zero = 0
