Plot two variables from experimental or other data (to include: sketching…

The idea

Plotting two variables from experimental or other data requires selecting an appropriate graph. For experimental data, a bar chart plots a categorical independent variable against a continuous dependent variable (e.g., mean words recalled for two groups). A line graph plots a continuous independent variable against a continuous dependent variable. You must also be able to sketch a scatter diagram using two sets of data from a correlational investigation. Each point represents a participant's scores on both co-variables. Axes must be clearly labelled and evenly scaled. The plot is analysed for the direction and strength of the relationship; points rising from left to right indicate a positive correlation.

What earns the marks

• Accurately plotting two variables from experimental data, selecting bar charts for categorical independent variables and line graphs for continuous variables.
• Sketching a scatter diagram using two sets of data from a correlational investigation by plotting one point for each participant where their two scores intersect.
• Ensuring both axes on a scatter diagram are clearly labelled with the co-variables and feature evenly spaced numerical scales.
• Identifying the relationship shown by the points (positive, negative, or zero correlation) and expressing it in terms of the specific co-variables.
• Recognising that a scatter diagram displays an association between two measured variables and cannot be used to establish a cause-and-effect relationship.

Common mistakes and how to put them right

• Connecting the points in a scatter diagram with a line in the order they were plotted.

  Put it right: Leave the individual points unconnected to accurately represent a correlational investigation.

• Using a scatter diagram to plot experimental data that features a categorical independent variable.

  Put it right: Select a bar chart to plot a categorical independent variable against a continuous dependent variable.

• Using causal language when interpreting a scatter diagram, such as stating one variable 'caused' a change in the other.

  Put it right: Use associative language, as correlational data does not involve manipulation of variables.

Exam tips

• When instructed to sketch a scatter diagram using two sets of data from a correlational investigation, always include a descriptive title and ensure your axis scales are linear and evenly spaced.
• If asked to interpret a scatter diagram, explicitly state the direction (e.g., positive) and strength (e.g., strong) of the correlation, referencing the specific co-variables plotted.