Cambridge IGCSE ICT 0417 – Graphs and ChartsTopic 16 – Graphs and Charts
Objective
Be able to select the most appropriate graph or chart type for a given set of data.
Why Choose the Right Graph?
Choosing the correct visual representation helps the audience to:
- Understand trends and patterns quickly.
- Compare values accurately.
- Interpret relationships between variables.
- Make informed decisions based on the data.
Common Graph and Chart Types
- Bar Chart – compares discrete categories.
- Column Chart – similar to a bar chart but vertical; useful for time‑based data.
- Line Graph – shows trends over continuous intervals (e.g., months, years).
- Pie Chart – displays parts of a whole as percentages.
- Scatter Plot – shows relationship between two quantitative variables.
- Histogram – shows frequency distribution of a single quantitative variable.
- Area Chart – like a line graph but fills the area below the line; good for cumulative totals.
- Stacked Bar/Column Chart – compares total size of categories and the contribution of sub‑categories.
Comparison of Graph Types
| Graph / Chart Type | Best For | Data Type | Typical Example |
|---|
| Bar Chart | Comparing individual categories | Nominal / ordinal | Sales of different products in a month |
| Column Chart | Comparing categories over time | Nominal with time series | Quarterly revenue per region |
| Line Graph | Showing trends or changes | Continuous (time) | Temperature changes over a year |
| Pie Chart | Displaying parts of a whole | Percentages / fractions | Market share of five companies |
| Scatter Plot | Examining correlation between two variables | Two quantitative variables | Height vs. weight of students |
| Histogram | Showing frequency distribution | Continuous quantitative | Distribution of test scores |
| Area Chart | Cumulative totals over time | Continuous (time) | Total website visitors per month |
| Stacked Bar/Column Chart | Comparing totals and sub‑components | Nominal with sub‑categories | Sales by product line and region |
Steps to Select the Appropriate Graph
- Identify the purpose of the visualisation (compare, show trend, illustrate proportion, etc.).
- Determine the type of data you have (categorical, ordinal, continuous, percentages).
- Consider the number of variables:
- One variable – bar, column, pie, histogram.
- Two variables – line, scatter, area.
- More than two – stacked charts or multiple series.
- Check the audience’s familiarity with the graph type.
- Choose a graph that presents the data clearly without distortion.
Example Scenarios
- Scenario A: A school wants to show the percentage of students achieving each grade (A, B, C, D, E).
Best choice: Pie Chart – clearly displays parts of the whole.
- Scenario B: A company tracks monthly sales over the last three years.
Best choice: Line Graph – highlights trends and seasonal patterns.
- Scenario C: A researcher compares the number of visitors to five different museums.
Best choice: Bar Chart – easy side‑by‑side comparison.
- Scenario D: An analyst examines the relationship between advertising spend and revenue.
Best choice: Scatter Plot – shows correlation and possible outliers.
Key Points to Remember
- Use a pie chart only when the total adds up to 100 % and there are few categories.
- Use a line graph for continuous data over time; avoid it for unrelated categories.
- Bar and column charts are interchangeable; choose orientation based on space and readability.
- Scatter plots require both axes to be quantitative; they are not suitable for categorical data.
- Histograms group data into intervals; they differ from bar charts because the bars touch each other.
Suggested Diagram
Suggested diagram: A decision flowchart that guides the user through the steps of selecting a graph type based on data characteristics.
Practice Exercise
For each of the following data sets, state which graph type would be most appropriate and justify your choice.
- Number of books sold by genre (Fiction, Non‑fiction, Mystery, Science, Biography).
- Average daily temperature recorded over a 12‑month period.
- Proportion of budget allocated to marketing, research, operations, and administration.
- Relationship between hours studied and exam score for a group of students.
- Frequency of test scores grouped in intervals of 10 points (0‑10, 11‑20, …, 91‑100).