Experiments in Sociology – An Introduction

Experiments aim to measure the effect which an independent variable (the ’cause’) has on a dependent variable (‘the effect’).

The key features of an experiment are control over variables, precise measurement, and establishing cause and effect relationships.

In order to establish cause and effect relationships, the independent variable is changed and the dependent variable is measured; all other variables (known as extraneous variables) are controlled in the experimental process.

Different types of experiment

There are three main types of experimental: 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.

The Key Features of the Experiment

It’s easiest to explain what an experiment is by using an example from the natural sciences, so I’m going to explain about experiments further using an example used from biology

NB – You do need to know about the scientific method for the second year sociology theory and methods part of the course ( for an overview of theories and methods click here), so this is still all necessary information. I’ll return to the use of laboratory and field experiments in sociology (/ psychology) later on…

An example to illustrate the key features of an experiment

If you wished to measure the precise effect temperature had on the amount* of tomatoes a tomato plant produced, you could design an experiment in which you took two tomato plants of the same variety, and grow them in the same greenhouse with same soil, the same amount of light, and the same amount of water (and everything else exactly the same), but grow them on different heat pads, so one is heated to 15 degrees, and the other 20 degrees (5 degrees difference between the two).

You would then collect the tomatoes from each plant at the same time of year** (say in September sometime) and weigh them (*weighing would be a more accurate way of measuring the amount of tomatoes rather than the number produced), the difference in weight between the two piles of tomatoes would give you the ‘effect’ of the 5 degree temperature difference.

You would probably want to repeat the experiment a number of times to ensure good reliability, and then average all the yields of tomatoes to come up with an average difference.

After, say, 1000 experiments you might reasonably conclude that if you grow tomatoes at 20 degrees rather than 15 degrees, each plant will give you 0.5 kg more tomatoes, thus the ’cause’ of the 5 degree temperature increase is 0.5 Kg more tomatoes per plant.

In the above example, the amount of tomatoes is the dependent variable, the temperature is the independent variable, and everything else (the water, nutrients, soil etc. which you control, or keep the same) are the extraneous variables.

** of course, you might get different results if you collected the tomatoes as they ripened, but for the sake of controlling extraneous variables, you would need to collect all the tomatoes at the same time.

The Role of Hypotheses in Experiments

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 specific, testable statement about the effect which one or more independent variables will have on the dependent variable.

The point of using a hypothesis is that it helps with accuracy, focussing the researcher in on testing the specific relationship between two variables precisely, it also helps with objectivity (see below).

Having collected the results from the above experiment, you might reasonably hypothesise that ‘a tomato plant grown at 25 degrees compared to 20 degrees will yield 0.5K.G. more tomatoes’ (in fact a proper hypothesis would probably be even tighter than this, but hopefully you get the gist).

You would then simply repeat the above experiment, but heating one plant to 20 degrees and the other to 25 degrees, repeat 1000 (or so times) and on the basis of your findings, you could either accept or reject and modify the hypothesis.

Experiments and Objectivity

A further key feature of experiments are that they are supposed to produce objective knowledge – that is they reveal cause and effect relationships between variables which exist independently of the observer, because the results gained should have been completely uninfluenced by the researcher’s own values.

In other words, somebody else observing the same experiment, or repeating the same experiment should get the same results. If this is the case, then we can say that we have some objective knowledge.

A final (quick) word on tomato experiments, and objective knowledge…

NB – the use of tomato plants is not an idle example to illustrate the key features of the experiment – nearly everyone eats tomatoes (unless you’re the minority of Ketchup and Dolmio abstainers) – and so there’s a lot of profit in producing tomatoes, so I imagine that hundred of millions, if not billions of dollars has been spent on researching what combinations of variables lead to the most tomatoes being grown per acre, with the least inputs…. NB there would have to be a lot of experiments because a lot of variables interact, such as type of tomato plant, altitude, wave length of light, soil type, pests and pesticide use, as well as all of the basic stuff such as heat, light, and water.

A woman picks tomatoes at a desert experimental farming greenhouse.

The importance of objective, scientific knowledge about what combination of variables has what effect on tomato production is important, because if I have this knowledge (NB I may need to pay an agricultural science college for it, but it is there!) I can establish a tomato farm and set up the exact conditions for maximum production, and predict with some certainty how many tomatoes I’ll end up with in a season…(assuming I’m growing under glass, where I can control everything).

In summary so far… the general advantages of the experimental method

  • It allows us to establish ’cause and effect relationships’ between variables.
  • It allows for the precise measurement of the relationship between variables, enabling us to make accurate predictions about how two things will interact in the future.
  • The researcher can remain relatively detached from the research process, so it allows for the collection of objective knowledge, independent of the subjective opinions of the researcher.
  • It has excellent reliability because controlled environments allow for the exact conditions of the research to be repeated and results tested.

Disadvantages of the experimental method/ why it may not be applicable to studying society as a whole or even individual humans…

  • There are so many variables ‘out there’ in the real world that it is impossible to control and measure them all.
  • Most social groups are too large to study scientifically, you can’t get a city into a laboratory to control all it’s variables, you couldn’t even do this with a field experiment.
  • Human beings have their own personal, emotionally charged reasons for acting, which often they don’t know themselves, so they are impossible to measure in any objective way.
  • Human beings have consciousness and so don’t just react in a predictable way to external stimuli: they think about things, make judgements and act accordingly, so it’s impossible to predict human behaviour.
  • There are also ethical concerns with treating humans as ‘research subjects’ rather than equal partners in the research process.

June 2017 – In the middle of updating this, I promise I’ll get onto experiments in sociology shortly!

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.

Related Posts 

Laboratory experiments: definition, explanation, advantages and disadvantages

Field experiments: definition, explanation, advantages and disadvantages.

Useful Introductory Sources on Experiments

Simply Psychology – The Experimental Method

 

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5 Responses to Experiments in Sociology – An Introduction

  1. Pingback: Field Experiments: Definition, Examples, Advantages and Disadvantages | ReviseSociology

  2. Pingback: Laboratory Experiments: Definition, Explanation, Advantages and Disadvantages | ReviseSociology

  3. Pingback: Seven Examples of Field Experiments for Sociology | ReviseSociology

  4. Pingback: Experiments in Sociology – Revision Notes | ReviseSociology

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