Scatter Graphs

Overview of Scatter Graphs

• A scatter graph is a diagram where each value in the data set is represented by a dot.
• The position of a dot on the horizontal and vertical axis indicates values for an individual data point.
• Scatter graphs are used to present the relationship between two variables in a set of data.

Creating Scatter Graphs

• Draw a horizontal axis (x-axis) and a vertical axis (y-axis), which represent the two data sets you’re comparing.
• Label each axis with the variable it represents.
• Plot each pair of values as a point on the graph where the values on the x-axis and y-axis intersect.

Interpreting Scatter Graphs

• Look for a trend or pattern in the points, as this shows a relationship between the variables.
• If the points rise from left to right, this implies a positive correlation.
• If the points fall from left to right, this infers a negative correlation.
• If there is no apparent pattern and the points are dispersed randomly, then there’s no correlation.
• A line of best fit can be drawn to summarise the trend in the scatter graph.

Using Scatter Graphs for Predictions

• Scatter graphs can be used to predict values within the range of data.
• Draw a line of best fit and extend it beyond the range of data on the graph, then use this line to make an estimation or prediction.
• Remember, predictions outside the range of given data are less reliable.

Extraneous Variables

• Scatter graphs only show correlations, not causation.
• Any apparent relationship might be affected by an extraneous variable that isn’t included in the graph.
• It’s important not to make strong claims based on scatter graphs alone.