Evaluating

Shini and Simon present steps that should be taken when evaluating a science investigation

The final stage is to consider what has been learned from the investigation and the quality of the data. If it is decided that the experiment could have been improved in some way; suggestions should be considered of how and why.

Drawing conclusions

In this part you will say what your results show, and how this relates to the prediction you made at the start of the investigation.

Evaluating data

You need to consider if the data is of high quality. As well as looking at accuracy of the results, you can also consider reliability, repeatability and reproducibility.

An accurate result is one judged to be close to the true value. Accuracy can be improved by using appropriate, high quality measuring apparatus and by using the apparatus skilfully.

Reliability is affected by the number of results taken, including repeat readings where appropriate and the range of results collected.

Results are said to be repeatable if similar results are obtained when you repeat your investigation. To check reproducibility, you need to get someone else to follow your method and see if their results are similar to yours.

If the data is considered to not be of high quality then the method used might not be suitable.

Suggesting improvements

How accurate were your results? If there are sources of error then they will not be close to the true value and so not accurate. There are different sources of error:

  • Random errors are due to things you have no control over, such as a change in room temperature whilst you were collecting the results and reaction time when starting and stopping a stopwatch. Repeating your measurements and finding a mean will reduce the effect of random errors.
  • Systematic errors are due to problems with the equipment you used. For example, the balances you used may not have been set to zero at the start of the experiment and be out by 0.1 g for every measurement.

When discussing how to improve your investigation you may consider how to remove these sources of error and how to better use the equipment to make sure your readings are more accurate.

You may also decide that to see a clearer pattern in the results you need to take more measurements and what values these will take.