Experiments aim to measure the effect which one or more independent variables have on a dependent variable. The aim is to isolate and measure as precisely as possible the exact effect independent variables have on dependent variables
For example, if you grow tomato plants as a hobby and wanted to find out the effect which the amount of water, the temperature, and the amount of light has on the amount of tomatoes each plant produces you could design a series of experiments in which you varied the amount of light etc. and then measure the effects on the amount of fruit produced.
In the above example, the amount of tomatoes is known as the dependent variable and the water, the temperature and the amount of light are the independent variables.
Experiments typically start off with a hypothesis which is a theory or explanation made on the basis of limited evidence as a starting point for further investigation. A hypothesis will typically take the form of a testable statement about the effect which one or more independent variables will have on the dependent variable.
For example ‘tomato plants grown at a temperature of 21 degrees will produce more tomatoes than plants grown at 20 degrees.’
The above is a relatively simple hypothesis and testing it out is relatively straightforward – You would simply have to put a sample of tomato plants in an area heated to 21 degrees (known as the experimental group), and another sample in an area heated to 20 degrees (known as the control group). If you wanted to measure the precise effect temperature had on the amount of tomatoes produced, you would need to keep all other variables such as the amount of water, the type of soil etc. exactly the same, and only change the single variable of temperature (by 1 degree).
NB – This isn’t an idle example – tomatoes are one of the most popular fruits in the world, and agricultural scientists have conducted thousands of experiments to find the ideal growing conditions for different varieties of tomatoes where they manipulate combinations of independent variables.
Different types of experiment
There are three main types of experimental method: The Laboratory experiment, the field experiment and the comparative method.
Laboratory Experiments take place in an artificial, controlled environment such as a laboratory
Field Experiments – take place in a real world context such as a school or a hospital.
The comparative method – involves comparing two or more similar societies or groups which are similar in some respects but varied in others, and looking for correlations.
Experiments – Key Terms
Hypothesis – a theory or explanation made on the basis of limited evidence as a starting point for further investigation. A hypothesis will typically take the form of a testable statement about the effect which one or more independent variables will have on the dependent variable.
Dependent Variable – this is the object of the study in the experiment, the variable which will (possibly) be effected by the independent variables.
Independent variables – The variables which are varied in an experiment – the factors which the experimenter changes in order to measure the effect they have on the dependent variable.
Extraneous variables – Variables which are not of interest to the researcher but which may interfere with the results of an experiment
Experimental group – The group under study in the investigation.
Control group – The group which is similar to the study group who are held constant. Following the experiment the experimental group can be compared to the control group to measure the extent of the impact (if any) of the independent variables.
External Validity – The extent to which the conditions of an experiment reflect real life. Laboratory experiments have lower external validity than field experiments.
The Hawthorne Effect – Where respondents act differently and try to please the researcher because they know they are part of an experiment.
Positivism, Interpretivism and Experiments
Positivists favour the laboratory experiment in principle because of the following reasons:
It has excellent reliability
It allows us to establish ’cause and effect relationships’ between variables
It allows for the collection of objective knowledge – about how facts out there effect individuals.
It allows for the researcher to remain relatively detached from her research subjects.
However Positivists also recognise the following limitations:
They are small scale and thus unrepresentative
They don’t allow for the study of large scale social processes
For this reason Positivists try to use methods which are as close the the experimental method as possible – namely the comparative method using quantitative data.
Interpretivists reject the laboratory experiment on the following basis:
They take place in artificial environments and so don’t reflect real social contexts, and thus lab experiments fail to achieve the Interpretivists main goal of validity.
They are reductionist – they try to explain human behaviour in terms of simple causes and effects – in reality, the reasons why people act in the way they do are more complex, and we need to understand these complexities to understand people (by using more qualitative methods)
In experiments, the researcher takes on the role of the expert, who decides what is worth knowing in advance of the experiment. In the real world, respondents have free-will and are unpredictable – thus they can easily defy the predictions made as a result of experimental knowledge.
Interpretivists are uncomfortable with the unequal relationships between researcher and respondent.
Interpretivists prefer field experiments over lab experiments because of their more naturalistic settings, but would treat even these with caution.
laboratory experiments: definition, explanation, advantages and disadvantages
Field experiments: definition, explanation, advantages and disadvantages.