Error analysis in biology is no different from that in other sciences. Biology however is not an “exact” science in that much of the data collected by biologists is qualitative. Furthermore, biological systems are very complex and difficult to control. Biological investigations, nevertheless, do often require measurements and biologists do need to be aware of the sources of error in their data.

Human error:  Obviously data which is carefully recorded will be more reliable than data collected carelessly.  Human error can occur when tools or instruments are used or read incorrectly. For example, a temperature reading from a thermometer in a liquid should be taken after stirring the liquid and whilst the bulb of the thermometer is still in the liquid. Thermometers and other instruments should be read with the eye level with the liquid otherwise this results in parallax error. Human errors can be systematic because the experimenter does not know how to use the apparatus properly or they can be random because the power of concentration of the experimenter is fading.

Systematic errors:  If an electronic water bath is set to 37°C the thermometer in the water bath should also read 37°C. If they do not agree then there will be an error at any other temperature being used. Some instruments need calibrating before you use them. If this is done correctly and regularly it can reduce the risk of systematic error.

Random errors:  In biological investigations, the changes in the material used or the conditions in which they are carried out can cause a lot of errors. Biological material is notably variable.  For example, the solute concentration of potato tissue may be calculated by soaking pieces of tissue in a range of concentrations of sucrose solutions. However, different pieces of tissue will vary in their water potential especially if they have been taken from different potatoes.  The problem of random errors can be kept to a minimum by careful selection of material and careful control of variables (e.g. using a water bath or a blank).  As we saw above, human errors can become random when you have to make a lot of tedious measurements, your concentration span can vary. Automated measuring using a data-logger system can help reduce the likelihood of this error; alternatively you can take a break from measuring from time to time.

The act of measuring:  When a measurement is taken this can affect the environment of the experiment.  For example when a cold thermometer is put in a test tube of warm water, the water will be cooled by the presence of the thermometer. When the behavior of animals is being recorded the presence of the experimenter may influence them.