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Laboratory Experiments in sociology

A summary of the practical, ethical and theoretical advantages and disadvantages of lab experiments

This post focuses on the practical, theoretical and ethical and strengths and limitations of laboratory experiment, applied mainly to sociology…

What are laboratory Experiments?

Laboratory experiments take place in controlled environments and are the main method used in the natural sciences such as Physics, Chemistry and Biology. There are numerous experiments which have been designed to test numerous scientific theories about the temperatures at which various substances freeze or melt, or how different chemicals react when they are combined under certain conditions.

The logic of the experimental method is that it is a controlled environment which enables the scientist to measure precisely the effects of independent variables on dependent variables, thus establishing cause and effect relationships. This in turn enables them to make predictions about how the dependent variable will act in the future.

For a general introduction to the key features of experiments and the experimental method (including key terms such as hypothesis and dependent and independent variables) and some of their advantages please see this post: experiments in sociology: an introduction.

The laboratory experiment and is commonly used in psychology, where experiments are used to measure the effects of sleep loss and alcohol on concentration and reaction time, as well as some more ethically dubious experiments designed to measure the effects of media violence on children and the responses of people to authority figures.

However, they are less common in sociology. Having said that, they are still a requirement within the research methods component of A-level sociology and the AQA exam board does seem to like setting exam questions on experiments!

Laboratory Experiments: Theoretical Factors

Theoretical Advantages of Laboratory Experiments

Accuracy and Precision– Laboratory experiments allow the precise effects of independent variables on dependent variables to be measured. This in turn makes it possible to establish cause and effect relationships between variables.

Isolation of Variables – The controlled conditions of laboratory experiments allows researchers to isolate variables more effectively than with any other research method. This further allows researchers to precisely measure the exact effect which one or more independent variables have on the dependent variable. With the ‘tomato experiment’ for example, laboratory conditions would allow the researcher to control precisely variations in temperature, moisture and light, this would not be possible in a field (no pun intended).

Controlled conditions also allow the researchers to eliminate the effects of ‘extraneous variables’. Extraneous variables are undesirable variables which are not of interest to the researcher but might interfere with the results of the experiment. If you were trying to measure the effects of alcohol on reaction time for example, keeping respondents in a lab means you could make sure they all at and drank similar things, and did similar things, in between drinking the alcohol (or placebo) and doing the reaction time test.

Laboratory experiments have excellent reliability for two major reasons:

Firstly, the controlled environment means it easy to replicate the exact environmental conditions of the original experiment and this also means it is relatively easy for the researcher to clearly outline the exact stages of the experiment, again making exact replication easier. This is not necessarily the case in a field experiment, where extraneous variables may interfere with the research process in different ways with repeat-experiments.

Secondly, there is a high level of detachment between the researcher and the respondent. In an experiment, the researcher typically takes on the role of ‘expert’ and simply manipulates variables, trying to have as little interaction with the respondents as the experiment will allow for. This means there is little room for the researcher’s own values to influence the way the respondent reacts to an experiment.

Theoretical Limitations of Laboratory Experiments

Laboratory experiments lack external validity – sociologists hardly ever use lab experiments because the artificial environment of the laboratory is so far removed from real-life that most Sociologists agree that the results gained from such experiments tell us very little about how respondents would actually act in real life. Take the Milgram experiment for example – how likely is it that you will ever be asked by scientist to give electric shocks to someone you’ve never met and who you can’t see when they give the wrong answer to a question you’ve just read out? Moreover, when was they last time you were asked to do anything to anyone by a scientist? In the real world context, many of the Milgram respondents may have responded to real-world authority figure’s demands differently.

Laboratory Experiments: Practical Factors

The practical advantages of lab experiments

In terms of practical advantages experiments (assuming they are ethical) are attractive to funding bodies because of their scientific, quantitative nature, and because science carries with it a certain prestige.

Once the experiment is set up, if it takes place in a lab, researchers can conduct research like any other day-job – there is no travelling to visit respondents for example, everyone comes to the researcher.

The practical problems of lab experiments

Practical problems include the fact that you cannot get many sociological subjects into the small scale setting of a laboratory setting. You can’t get a large group of people, or a subculture, or a community into a lab in order to observe how the interact with ‘independent variables’.

Also, the controlled nature of the experiment means you are likely to be researching one person at a time, rather than several people completing a questionnaire at once, so it may take a long time to get a large-sample.

Laboratory Experiments: Ethical Factors

The ethical limitations of laboratory experiments

Deception and lack of informed consent are an ethical problem- The Hawthorne effect gives rise to the firs ethical disadvantages often found in experiments – it is often necessary to deceive subjects as to the true nature of the experiment so that they do not act differently, meaning that they are not in a position to give full, informed consent. This was the case in the Milgram experiment, where the research subjects thought the (invisible) person receiving the shocks was the actual subject rather than themselves.

A second ethical problem concerns harm to respondents. In the case of the original Milgram experiment, ‘many research participants were observed to sweat, stutter, tremble, bit their lips and dig their nails into their flesh, full-blown, uncontrollable seizures were observed for three subjects’.

The ethical strengths of laboratory experiments

While some laboratory experiments are notorious for their ethical problems, it is at least usually obvious that research is taking place (even if the exact purpose of the research may be hidden from respondents). Also, the benefits to society might well outweigh the costs to respondents.

The above material is mainly relevant to the research methods aspect of A-level sociology.

Intro to Experiments in Sociology

Field Experiments in Sociology

Sources/ References

Milgram’s Experiment on Obedience to Authority, which cites Milgram, S. (1974). Obedience to Authority: An Experimental View. New York: Harper and Row. An excellent presentation of Milgram�s work is also found in Brown, R. (1986). Social Forces in Obedience and Rebellion. Social Psychology: The Second Edition. New York: The Free Press.

Variables in quantitative reserach

What is the difference between interval/ ratio, ordinal, nominal and categorical variables? This post answers this question!

Interval/ ratio variables

Where the distances between the categories are identical across the range of categories.

For example, in question 2, the age intervals go up in years, and the distance between the years is same between every interval.

Interval/ ratio variables are regarded as the highest level of measurement because they permit a wider variety of statistical analyses to be conducted.

There is also a difference between interval and ratio variables… the later have a fixed zero point.

Ordinal variables

These are variables that can be rank ordered but the distances between the categories are not equal across the range. For example, in question 6, the periods can be ranked, but the distances between the categories are not equal.

NB if you choose to group an interval variable like age in question 2 into groups (e.g. 20 and under, 21-30, 31-40 and so on) you are converting it into an ordinal variable.

Nominal or categorical variables

These consist of categories that cannot be rank ordered. For example, in questions 7-9, it is not possible to rank subjective responses of respondents here into an order.

Dichotomous variables

These variables contain data that have only two categories – e.g. ‘male’ and ‘female’. Their relationship to the other types of variable is slightly ambiguous. In the case of question one, this dichotomous variable is also a categorical variable. However, some dichotomous variables may be ordinal variables as they could have one distinct interval between responses – e.g. a question might ask ‘have you ever heard of Karl Marx’ – a yes response could be regarded as higher in rank order to a no response.

Multiple-indicator measure such as Likert Scales provide strictly speaking ordinal variables, however, many writers argue they can be treated as though they produce interval/ ratio variables, if they generate large number of categories.

In fact Bryman and Cramer (2011) make a distinction between ‘true’ interval/ ratio variables and those generated by Likert Scales.

A flow chart to help define variables

*A nominal variable – aka categorical variable!

Questionnaire Example

This section deals with how different types of question in a questionnaire can be designed to yield different types of variable in the responses from respondents.

If you look at the example of a questionnaire below, you will notice that the information you receive varies by question

Some of the questions ask for answers in terms of real numbers, such as question 2 which asks ‘how old are you’ or questions 4 and 5 and 6 which asks students how many hours a day they spend doing sociology class work and homework. These will yield interval variables.

Some of the questions ask for either/ or answers or yes/ no answers and are thus in the form of dichotomies. For example, question 1 asks ‘are you male or female’ and question 10 asks students to respond ‘yes’ or ‘no’ to whether they intend to study sociology at university. These will yield dichotomous variables.

The rest of the questions ask the respondent to select from lists of categories:

The responses to some of these list questions can be rank ordered – for example in question 6, once a day is clearly more than once a month! Responses to these questions will yield ordinal variables.

Some other ‘categorical list’ questions yield responses which cannot be ranked in order – for example it is impossible to say that studying sociology because you find it generally interesting is ranked higher than studying it because it fits in with your career goals. These will yield categorical variables.

These different types of response correspond to the four main types of variable above.

Experiments in Sociology – Revision Notes

Definitions, key features and the theoretical, practical and ethical strengths and limitations of laboratory and field experiments applied to sociology (and psychology). Also covers key terms related to experiments.

post has been written to help students revising for the research methods aspect of their second year A-level exams.

Experiments – The Basics: Definitions/ Key Features

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.
Experiments typically aim to test a ‘hypothesis’ – a prediction about how one variable will effect another.
There are two 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.

Advantages of Laboratory Experiments

Theoretical – The controlled conditions of laboratory experiments allow researchers to isolate variables: you can precisely measure the exact effect of one thing on another.

Theoretical – You can establish cause and effect relationships.
Theoretical – You can collect ‘objective’ knowledge – about how facts ‘out there’ affect individuals.
Theoretical – Good Reliability because it is easy to replicate the exact same conditions.

Theoretical – Good Reliability because of the high level of detachment between the researcher and the respondent.
Practical – Easy to attract funding because of the prestige of science.
Practical – Take place in one setting so researchers can conduct research like any other day-job – no need to chase respondents.

Ethical – Most laboratory experiments seek to gain informed consent, often a requirement to get funding.
Ethical – Legality – lab experiments rarely ask participants to do anything illegal.
Ethical – Findings benefit society – both Milgram and Zimbardo would claim the shocking findings of their research outweigh the harms done to respondents.

Disadvantages of Laboratory Experiments

Theoretical – They are reductionist: human behaviour cannot be explained through simple cause and effect relationships (people are not ‘puppets’).
Theoretical – Laboratory experiments lack external validity – the artificial environment is so far removed from real-life that the results tell us very little about how respondents would actually act in real life.
Theoretical – The Hawthorne Effect may further reduce validity – respondents may act differently just because they know they are part of an experiment.

Theoretical – They are small scale and thus unrepresentative.
Practical – It is impractical to observe large scale social processes in a laboratory – you cannot get whole towns, let alone countries of people into the small scale setting of a laboratory.
Practical – Time – Small samples mean you will need to conduct consecutive experiments on small groups if you want large samples, which will take time

Ethical – Deception and lack of informed consent – it is often necessary to deceive subjects as to the true nature of the experiment so that they do not act differently. Links to the Hawthorne Effect.
Ethical – Some specific experiments have resulted in harm to respondents – in the Milgram experiment for example.
Ethical – Interpretivists may be uncomfortable with the unequal relationships between researcher and respondent – the researcher takes on the role of the expert, who decides what is worth knowing in advance of the experiment.

Advantages of Field Experiments over Laboratory Experiments

Theoretical – They generally have better validity than lab experiments because they take place in real life settings
Theoretical – Better external validity – because they take place in normally occurring, real-world social settings.
Practical – Larger scale settings – you can do field experiments in schools or workplaces, so you can observe large scale social processes, which isn’t possible with laboratory experiments.

Practical – a researcher can ‘set up’ a field experiment and let it run for a year, and then come back later.

The relative disadvantages of Field Experiments

Theoretical – It is not possible to control variables as closely as with laboratory experiments – because it’s impossible to observe respondents 100% of the time.
Theoretical – Reliability is weaker – because it’s more difficult to replicate the exact context of the research again.

Theoretical – The Hawthorne Effect (or Experimental Effect) may reduce the validity of results.
Practical Problems – access is likely to be more of a problem with lab experiments. Schools and workplaces might be reluctant to allow researchers in.
Ethical Problems – As with lab experiments – it is often possible to not inform people that an experiment is taking place in order for them to act naturally, so the issues of deception and lack of informed consent apply here too, as does the issue of harm.

Experiments – Key Terms Summary

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.

You should also know about natural experiments/ the comparative method –involves comparing two or more societies or groups which are similar in some respects but varied in others, and looking for correlations.

Signposting

This post has been written to help students revising for the research methods aspect of their second year A-level exams.

These are the more in-depth posts on experiments

Experiments in sociology – an introduction

Laboratory experiments in sociology

Field experiments in sociology

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).

The 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.

Experiments – Key Terms

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.

Laboratory experiments: definition, explanation, advantages and disadvantages

Field experiments: definition, explanation, advantages and disadvantages.

Useful Introductory Sources on Experiments

Simply Psychology – The Experimental Method