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A scatterplot shows the relationship between two quantitative variables measured for the same individuals. The values of one variable appear on the horizontal axis, and the values of the other variable appear on the vertical axis. Each individual in the data appears as a point on the graph.

A graph shows a strong positive correlation when the data points are close to a line and move steeply upwards. A weak positive correlation is when points somewhat move upwards but are dispersed around the line. Downward moving points indicate negative correlation, and no discernible pattern shows no correlation.

When we look at scatterplot, we should be able to describe the association we see between the variables. A quick description of the association in a scatterplot should always include a description of the form, direction, and strength of the association, along with the presence of any outliers.

The strength of a scatter plot is usually described as weak, moderate or strong. The more spread out the points are, the weaker the relationship. If the points are clearly clustered, or closely follow a curve or line, the relationship is described as strong.

As in any graph of data, look for the overall pattern and for striking departures from that pattern. The overall pattern of a scatterplot can be described by the direction, form, and strength of the relationship.

The more spread out the points are, the weaker the relationship. If the points are clearly clustered, or closely follow a curve or line, the relationship is described as strong. The linearity of scatter plot indicates how close the points are to a straight line. Scatter plots are described as linear or nonlinear.

You interpret a scatterplot by looking for trends in the data as you go from left to right: If the data show an uphill pattern as you move from left to right, this indicates a positive relationship between X and Y. As the X-values increase (move right), the Y-values tend to increase (move up).

Scatter graphs visually show the correlation between two variables. Correlation can vary in strength. Sometimes there is a strong relationship between data and other times the relationship is weak. You can see this visually on a scatter graph by observing how close the plots are together in forming a line.