Graphs and charts

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Key points

  • Different types of graphs and charts are needed to present results from experiments.
  • Graphs and charts need to be drawn and labelled correctly.
  • Use patterns in the data to reach a conclusion in an experiment.

True or false?

It is easier to see patterns in data from a graph than a table.

True.

Many people find graphs or charts much easier to understand. They can often see patterns or trends that are much harder to spot in tables of data.

How to pick the correct chart

Watch this video on how to choose a graph or chart and how to draw them.

While you are watching, look carefully at how scales are chosen for the graph or chart

Presenting data

After collecting and recording , scientists often put their data into a graph or a chart. This shows the data in a useful way and helps them to reach conclusions.

The most common ways of presenting data in science are and .

A line graph should be used when the independent and dependent variables are .

A bar chart should be used if the independent variable is .

or categoric data can also be shown on a pie chart. Pie charts are often used when using percentages of data to draw a graph.

If both the independent and dependent variables are continuous, how should data be presented?

With a line graph.

Drawing graphs and charts

When drawing a chart or a graph, the independent variable goes on the horizontal (x) axis and the dependent variable goes on the vertical (y) axis.

Once this has been identified, follow these steps:

  1. Choose scales for the axes so that the graph is as big as possible on the page.
  2. Use a pencil and a ruler to draw axes, bars, or to .
  3. Label the axes with the quantity and the unit, such as ‘Temperature, °C’.
  4. Write a title for the graph.

True or false?

Units are not needed when drawing a graph.

False.

Units are important, so always include them because they give us the scale. Imagine if the race you wanted to run was in miles not metres. Or the time of a car journey was in days not hours.

How to draw graphs and charts

Presenting data in a graph or chart needs to be done carefully. As well as the four steps described above, there are other things to think about.

A hand holding a pencil plots points on a piece of graph paper

When drawing a line graph, it’s important to look at the range for the data before drawing a simple scale. When plotting the ‘Xs’ on the graph, the data must be presented accurately.

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True or false?

A gap should be left between bars on a bar chart if the data is not continuous.

True.

If the independent variable is not continuous, leave a gap between each bar.

Analysing data

Finding patterns in data on a graph or chart is known as ‘interpreting relationships’. Plotting a chart or graph helps to show a pattern in the data - how the dependent variable depends on the independent variable.

Once points have been plotted for a line graph, draw a . The line should be drawn through as many points as possible, with equal numbers of points above and below the line. If there are any then these should be ignored when drawing the line of best fit.

A line graph showing an increase in temperature as time increases when you boil a kettle, the line curves towards the end showing a decrease in the speed of temperature increase.

Once the graph has been analysed, write a conclusion. Support a conclusion by saying what the graph shows, such as if there is a relationship between the two variables. A good way of describing the relationship is to say what happens to one variable as the other one increases or decreases. For example, the longer a kettle is left to boil, the hotter the water gets until it reaches 100°C.

A step-by-step guide on drawing a line of best fit

A graph with 2 axes labelled A and B with plotted points scattered at random

1. After plotting points on a graph, draw a line of best fit to present the data and make it easier to analyse. If there is no link between variables, then there will be no clear pattern of points and a line of best fit would not be drawn.

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What is the name of a result that should be ignored when drawing the line of best fit?

An outlier should be ignored when drawing a line of best fit.

Analysing trends in graphs

When data is analysed and a relationship between two variables is described, it's important to say how changing one variable affects the other. These line graphs show some common shapes that arise when the independent variable (A) affects the dependent variable (B).

A line graph with 3 lines on it, each an example of what path the line could follow if as A increases, B increases.
As A increases, B increases.

The yellow line is straight because each increase in A gives the same increase in B. This is also true in the straight parts of blue and red lines. When the blue line curves horizontally, the same increase in A gives a smaller increase in B. When the red line curves upwards, the same increase in A gives a greater increase in B.

A line graph with 3 lines on it, each an example of what path the line could follow if as A increases, B decreases
As A increases, B decreases.

The yellow line is straight because each increase in A gives the same decrease in B. This is also true in the straight parts of blue and red lines. When the blue line curves downwards, the same increase in A gives a greater decrease in B. When the red line curves horizontally, the same increase in A gives a smaller decrease in B.

A graph with a straight line coming from the y axis going horizontally to the x-axis
As A increases, B does not change.

The yellow line is straight because as A increases, there is no change in B.

On these graphs, which variable goes on the horizontal (x) axis?

The independent variable. The dependent variable goes on the vertical (y) axis.

Test your knowledge

Quiz - Graphs and charts

Did you know?

  • The earliest use of a pie chart is generally credited to Scottish engineer and political economist William Playfair in 1801.
  • More people heard of pie charts after the founder of modern nursing, Florence Nightingale, used them for things like showing death from diseases during the Crimean war.