Tables

In scientific publications, data is usually presented in only two ways. Tables in which the data is arranged to allow easy comparison and evaluation, and Figures which comprise diagrams, graphs, charts, etc.

Here, we will look at preparing tables and graphs, both of which are used to summarize information and to illustrate patterns or relationships. The object is to present the data in as clear a form as possible without unnecessary detail, yet without leaving out any relevant facts. Preparing tables and graphs requires some knowledge of accepted practice and some skill in designing the table or graph to best describe the information.

Graphs are particularly useful to present similarities or contrasts between experimental results and provide a visual impression of the relationship between variables. By observing a few simple rules, it is possible to present data in such a way that they can be comprehended both by yourself and the reader. This method is not the only way of presenting tables and graphs, but it does refer to methods successfully used to present scientific data. Before graphs are drawn, the data must be tabulated in some way.

Remember that you create a graph, rather than provide a table of numbers, for a variety of reasons:

1. to convey the information quickly,
2. to identify any trends which may not be apparent,
3. conveying any relationships that may exist between groups or series of numbers.

The following five points can act as a checklist for you to review your own graphs, to avoid some basic mistakes when converting tables of numbers to a graphic format. Click on the title of a point to open an good or bad example in a separate window.

1. Accuracy of presentation - the information must be presented so that it is not deceptive, and truly reflects the meaning of the data.
2. Clarity of message - the graph title should focus clearly on the message that you want people to gain from your presentation of the data.
3. Graphic appearance - the graph should attract and hold people's attention, be clear, crisp and feel "professional".
4. Simplicity of presentation - the information presented should be concise, make one point well and use, for example, direct labels where possible, to avoid the need to search for more information.
5. Targeting the audience - ensure that your graph is appropriate for your target group. Simplest is often best, but a complex graph may be more suitable if aiming it at a group needing some sophisticated analysis of the data.

Preparing Data Tables

Observations should be recorded in table form, whenever possible. Some guidelines for the construction of data tables are given here. An example is provided in Table 1.

1. Provide a title that completely describes the data contained in the table, as well as a unique number. Write a descriptive title that communicates the contents or the relationship among the entries in the table. Place them at the top of the table.
2. Draw lines around the main body and columns of the data table. The table should be organized so that similar items can be read vertically, not horizontally.
3. Place the column containing the manipulated variable (the factor that can be controlled by the investigator) before column(s) containing the responding variable(s). It should start at the lowest value and increase from top to bottom of the table. When time is the independent variable do not use the date or the hour unless these are significant to the experiment (e.g., if a study is being made of seasonal effects, date is significant; otherwise use age or elapsed time (hours or minutes) between each observation). Record data with the goal of making interpretations easy. For example, ordering from smallest to largest, measuring at regular time intervals, etc.
4. Label all rows and columns with a heading, including units in parentheses where necessary. Units should not be written in the main body of the table.
5. Record only observations in a data table. Calculations belong in an analysis table.
6. Any comments needed to explain or draw attention to important points should be placed below the table.

Here's an example of the way your data table should look:

Table 1. The Effect of Salinity on Catalase Reaction Rate.