Polarity, strength of correlation
for 8th grade

Polarity and strength of correlation for scatter graphs

Scatter graphs use dots or diagonal crosses to represent values that correlate the relationship between two variables. The scatter graph will indicate the degree to which the two variables are correlated (linked or related).

For instance, a scatter graph plotting altitude (x-axis) against Oxygen concentration (y-axis) will indicate a strong correlation between these two variables because Oxygen concentration reduces with altitude (the reason climbers can suffer from altitude sickness). On the other hand, a scatter graph plotting eye colour against exam results will show no correlation because these two variables have no causal relationship.

The polarity of a correlation can be characterised as "positive" or "negative". This indicates whether an imaginary straight line drawn through the points (a line of best fit) rises to the right (positive - as the x-axis variable increases, so does the variable on the y-axis) or falls to the right (negative - as the x-axis value increases, the y-axis variable decreases). So, thinking about our example of altitude plotted against Oxygen concentration, we will see a negative correlation because the concentration decreases as the altitude increases. A positive correlation would be seen if we plotted a child's age against shoe size: as their age increases, so does their shoe size.

The strength of a correlation can be characterised as "strong" or "weak". A strong correlation will be indicated on a scatter graph by points that closely follow a line of best fit. A weak correlation will show points that are more loosely concentrated around a line of best fit.

In this topic you are asked to decide which of the descriptions provided best describe the correlation between the variables plotted on the x and y axes. The possible options are:

• Strong positive correlation
• Strong negative correlation
• Weak positive correlation
• Weak negative correlation
• No correlation