Common graphs

Common graphs

Scatter Graphs
These are the most useful graphs for showing the relationship between two variables that are being investigated and any correlations between them.
The independent variable of the investigation is plotted on the X-axis and the dependent variable is plotted on the Y-axis; the results are then marked on the graph with a cross. A line of best fit is drawn onto the graph, this is a line through the centre of the results with an equal number of points above and below the line.
Scatter graphs clearly highlight a correlation between two variables if it is present, and lots of points can be plotted within a small space. However the line of best fit can suggest a misleading relationship and are not accurate due to the fact they are drawn by eye. Scatter graphs are quick and easy to construct, but are much more useful when a statistical test is applied to the data.

Line Graphs
Line graphs are most useful for displaying continuous data; they are particularly good for showing changes over time, in this way they can be used to predict future trends and "fill in gaps" where no data is present (however any predictions are only as accurate as the data plotted and the line drawn).
The independent variable (eg time, distance) is plotted on the X-axis and the dependent variable on the Y-axis, and results marked with a cross like scatter graphs. However, unlike scatter graphs, a line is then drawn freehand following th pattern of results and ignoring anomalous results, this line can curve and bend.
The scale of a line graph must be chosen carefully because the scale chosen can alter a graph dramatically. Two different line graphs can also be compared, but they can only be compared accurately if they have the same/similar scales.

There are different types of line graph showing different things:

• Simple

This is a basic line graph that displays one set of data and has only one line.

• Comparative

This shows more than one line on the same axis for comparison.

• Divergent

This is where data is displayed both sides of the X-axis, so positive and negative values are plotted on the same line. They are good for showing variation away from the mean, where the X-axis represents the mean value.

• Compound

This is where the line is split into different factors that make up different proportions of the total area under the graph. They are useful for showing percentages or proportions.


Bar Graphs (Bar Charts)
These are graphs used to display data that is in categories; they are the simplest presentation of the number of results in a data set. These graphs can only be used to show discrete data, that has distinct intervals between the reults eg 1,2,3 or 1, 1.5, 2, 2.5 etc.
The categories in the data set are plotted on the X-axis underneath the corresponding bar, and the number in that category is plotted on the Y-axis with the bar extending up to the correct number on the X-axis.
The scale must be chosen carefully to ensure that all the data can be plotted on the same graph, and a false origin may be required to do so. When the bars are coloured differently it makes the graph aesthetically pleasing and easier to interpret.

There are also different types of bar graph that show different things:

• Simple

This is the most simple bar graph where only one set of data is plotted; there will be a number of bars from the same data set.

• Comparative

This is where more than one set of data is plotted on the same graph. Above each category on the X-axis there will be more than one bar from different sets of data, this allows comparisons to be made between data sets. For example the total rainfall at different sites over the year, the months would be the different categories on the X-axis and the results from each site the different bars.

• Divergent

This is where the bars diverge above and below the X-axis, or either side of the Y-axis. This shows positive and negative values on the same graph, and they are useful for showing difference from the mean.

• Compound

This is where each bar is divided into different categories. The bars can be different heights, representing different total values and then divided into proportions, or the same height, and divided into percentages.