Practical skills

• When planning an investigation, you can identify dependent, independent and controlled variables. It is important that controlled variables are kept the same during an investigation.

• Measurements should be taken accurately by using equipment in the correct manner.

• It is important to consider accuracy and reliability when evaluating an experiment.

When scientists start to investigate something they usually have a hypothesis that they are testing.

This means they have an idea about what will happen when they explore something or take some readings, but they need the evidence to either confirm their thinking or suggest they need to think again.

From this they can make a prediction. It is easy to get mixed up between hypotheses and predictions.

For example, a hypothesis might be that a higher temperature increases the rate of a chemical reaction.

From this a prediction might be a reaction carried out at 60^oC will be faster than one carried out at 30^oC.

Often an experiment involves things that can change, known as variables.

Variables need to be identified, so they can then either be changed or controlled. There are three kinds of variable:

• Dependent – the variable that is measured during the investigation.

• Independent – the variable that is changed deliberately during the investigation.

• Controlled – the variables(s) that are kept the same during the investigation.

Scientists often want to find out if changing one variable makes a difference to other variables.

In most investigations the controlled variables are kept the same and only the independent variable is altered.

The effect of the independent variable on the dependent variable is measured during the investigation.

After planning an investigation, the next step is to think about what equipment to use, and how to conduct the experiment safely.

If certain chemicals are going to be used, the potential hazards need to be identified to ensure that they are used safely.

This might affect the concentrations of solutions or the quantities used and even whether those substances are used at all.

The hazards also need to influence the general running of the experiment and how the equipment is used.

The next step is to think about the most appropriate equipment to use.

For example, the volume of a liquid could be measured using a beaker, a measuring cylinder or a burette.

In different circumstances one of these might be safer or more accurate than others, which would affect the choice.

If you need to measure out 5 cm³ of liquid then a 10 cm³ measuring cylinder would give a more accurate volume then using a 100 cm³ measuring cylinder.

Also, using balances that measure mass to the nearest 0.01 g will give a more accurate measurement then using ones that measure mass to the nearest gram.

When using observations to collect data during an experiment it is important to be as accurate as possible.

For example, when reading a burette during a titration, it is important to take the readings at eye level and from the bottom of the meniscus.

Data collected during an investigation is normally displayed in a results table.

At this point you can study your repeats to see how close they are. Repeats that are similar are said to be precise.

Sometimes you may have an anomalous repeat.

If this is the result of a measurement error it can be ignored, although it is good practice to repeat that measurement again.

The repeat measurements should be used to calculate a mean of the results.

It can be difficult to see the relationship between the variables from a results table so often the means are plotted on a graph or chart to analyse the results further.

It is important to choose the most appropriate type of graph or chart.

If both the independent and dependent variables are continuous data, then a line graph (also called a scatter graph) is the best choice.

Usually, a line of best fit will be drawn to show the trend in the data. This will allow you to see the relationship between the variables, for example if they are proportional (straight line through the origin).

Also, you can see if any of the values are anomalous as they will be placed far away from the line of best fit and do not follow the trend.

Results that are clearly anomalous can be ignored or repeated in the experiment.

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 as to 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.

You need to consider if the data is of high quality.

Two factors to consider are the accuracy and the reliability of the data.

Accuracy is a measure of how close your data reading is to the true value.

This is partially determined by how careful you are with your readings, but also how appropriate your equipment is for the measurement.

For example, using the scale lines on a beaker would be an inaccurate way of measuring the volume of a liquid.

Reliability is a measure of how repeatable your results are. You should aim to take multiple readings and calculate an average to obtain reliable data.

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. 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 have been 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.