INTRODUCTION TO CHEMISTRY | My Assignment Tutor


CHEMISTRY
TERM 1 – INTRODUCTION TO CHEMISTRY

LESSON 5

EXPERIMENTAL TECHNIQUES

Initial Planning

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.

Variables

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 3 kinds of variable:

Independent variable – the variable that is altered during a scientific experiment.

Dependent variable – the variable being tested or measured during a scientific experiment.

Controlled variable – a variable that is kept the same during a scientific experiment. Any change in a controlled variable would invalidate the results.

Scientists often want to find out if changing one variable makes a difference to other variables. In many (though not all) investigations the variables are kept constant – the control variables, apart from one which is varied – the independent variable. The effects of the independent variable are then determined by monitoring the dependent variable.

An example would be investigating whether increasing the temperature of the reactants might alter the rate of the reaction. As it is the temperature which is changing, that would be the independent variable. The changing temperature alters the rate of reaction, therefore the reaction rate is the dependent variable. When carrying out the experiment, care has to be taken that other variables that affect the rate of reaction, such as concentration of reactants, are kept constant. These are control variables.

Values and readings

The values are the measurements used for the independent variable. If, for example, one of the variables in an experiment was length, it would be important to decide the maximum and minimum values, and also the intervals between values. If enzyme activity at different pH values was being investigated, a decision would have to be made on what values of pH to use. This decision would take into account elements such as available equipment, time constraints, and safety.

When measurements are being taken, it is usually appropriate to repeat them. Sometimes, there are lots of possible readings that could be taken. For example if the distribution of daisies on a playing field was being explored, it wouldn’t be necessary to count every one; however, it wouldn’t be a good idea to just look at the ones close to the fence. A sampling technique should be used to decide which ones to look at. It might, for example, involve the method of randomly placing quadrats. A mean is then calculated.

Equipment Planning

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’re 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.

Observation

The experiment should be conducted in a clear and systematic way to ensure the data is complete and of a high quality. In an experiment into the relationship between force, mass and acceleration a toy car of different masses runs down a ramp. The acceleration needs to be measured several times at each mass. The repeats would all need to be done in the same way and with care to ensure precise data. If you observe that a repeat is not similar to the others then it is good idea to repeat it.

It is also important to pay careful attention while the experiment is being carried out. It might be that the car starts to deviate from a straight line path; which if significant may mean that the method should be modified.

Taking accurate measurements

When using observations to collect data during an experiment it is important to be as accurate as possible. For example, a reaction commonly used to investigate rate is between sodium thiosulfate and hydrochloric acid. The reaction takes place in a conical flask standing on a piece of paper where a cross has been drawn. At first, it is easy to see the cross through the reaction mixture. However, during the reaction the solution becomes cloudy. The time taken for the cross to become completely obscured is used as a way of measuring the rate of reaction. Different people might make the call as to whether the cross has been completely obscured at slightly different points so it might be decided to use the same person to make all the observations.

Analysing

Studying the data

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.

How to display the data

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.

Also, you can see if any of the values are anomalous as they will be placed far away from the line of best fit. An example of where a line graph would be used is in an investigation to see if temperature affects the rate of a reaction.

A bar chart is used if the independent variable has different categories. For example, to display the frequency of different eye colours in a group of people.

Evaluating

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 precision of the results, you can also consider repeatability and reproducibility.

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. 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.

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.

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