Bar Graphs: Used for comparing different groups or tracking changes over time for discrete variables. Compound Bar Charts further divide each bar to show sub-categories within a total.
Line Graphs: Ideal for displaying continuous data and identifying trends or patterns over a sequence, such as time or distance along a transect.
Scatter Graphs: Used to investigate the relationship between two numerical variables. A Line of Best Fit is often added to indicate the direction and strength of the correlation.
Rose Diagrams: Specialized circular graphs used for directional data, such as wind direction or the orientation of pebbles. The length of each 'petal' represents the frequency or magnitude in that direction.
Triangular Graphs: Used when data can be broken down into exactly three components that sum to 100% (e.g., soil texture composed of sand, silt, and clay).
| Method | Data Type | Primary Use Case |
|---|---|---|
| Bar Chart | Discrete / Categorical | Comparing distinct groups or totals |
| Line Graph | Continuous | Showing trends and changes over time |
| Scatter Plot | Two Numerical Variables | Identifying correlations and relationships |
| Rose Diagram | Directional | Showing frequency relative to compass points |
| Triangular Graph | Three-part Percentages | Showing composition of a whole |
Check the Basics: Always ensure your graph has a clear, descriptive title, labeled axes with units, and a key if multiple data series are present.
Scale Selection: Choose a scale that allows the data to fill most of the graph area. Avoid starting the y-axis at a high value unless clearly indicated, as this can exaggerate small differences.
Best-Fit Lines: In scatter graphs, ensure the line of best fit has an equal distribution of points above and below it. Do not simply connect the first and last points.
Precision in Plotting: Use a sharp pencil and ensure points are plotted accurately. In exams, marks are often awarded for the precision of specific data points.
Confusing Bar and Histograms: Bar charts have gaps between bars to represent discrete categories, while histograms have touching bars to represent continuous data ranges.
Inappropriate Graph Choice: Using a line graph for discrete categories (like 'City A' and 'City B') is a common error; lines imply a continuous transition between points that does not exist for discrete data.
Over-plotting: Adding too many data series to a single line graph or scatter plot can make it unreadable. If the visual is cluttered, consider using multiple smaller graphs (small multiples).
Ignoring Outliers: Students often try to force a line of best fit through an outlier. Outliers should be plotted but may be excluded from the trend line if they represent anomalies.
