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The Scientific Method in Psychology

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Presentation on theme: "The Scientific Method in Psychology"— Presentation transcript:

1 The Scientific Method in Psychology
How do we collect our data? Case studies

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Case studies Case studies are in-depth investigations of a single person, group, event or community. Case studies are not a unique research method, they simply use other research methods in a quest for drawing a conclusion.

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Case studies Variables are not systematically controlled or altered as in single-case experimental designs. Case studies are simply in-depth detailed analysis of individuals or close-knit groups of people as in a family unit.

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Case studies Sometimes case studies form longitudinal studies. This type of study extends over a period of time. The researcher studies the same individual or unit of individuals for a fixed amount of time (e.g. five years)

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Case studies This allows for an analysis of the development of behaviour over a time period. They don’t have to be exclusively about one person or unit of individuals. They can involve following a cohort (group) of people for the purposes of analysing the development of behaviour.

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Strengths of case studies As researchers are focusing on one individual (or unit of individuals) they can collect rich, in-depth data that has details – this makes the findings more valid. Participants are usually studied as part of their everyday life, which means that the whole process tends to have ecological validity.

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Weaknesses of case studies As researchers are focusing on one individual (or unit of individuals), the case may be unique. This makes generalisations quite difficult.

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Weaknesses of case studies As participants are studied in depth, an attachment could form between them and the researcher which could reduce the objectivity of the data collection and analysis of data. This could reduce the validity of the findings.

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Experimental design Researchers who choose to use an experiment have to decide on an experimental (participant design). This refers to how they allocate participants to the varying conditions of their experiment.

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Experimental design An experimental design is a set of procedures used to control the influence of participant variables so that we can investigate the possible effects of the independent variable on the dependent variable. There are three basic experimental designs: independent measures design, repeated measures design and matched pairs design.

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Independent measures design An independent measures design consists of using different participants for each condition of the experiment. If two groups in an experiment consist of different individuals then this is an independent measures design.

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Independent measures design

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Independent measures design For example, if we are trying to discover if girls are less aggressive than boys, then we obviously need 2 separate groups, namely boys and girls.

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Independent measures design strengths This type of design has an advantage resulting from the different participants used in each condition - there is no problem with order effects

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Independent measures design weaknesses The most serious disadvantage of independent measures designs is the potential for error resulting from individual differences between the groups of participants taking part in the different conditions.

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Independent measures design weaknesses Also an independent groups design may represent an uneconomic use of those participants, since twice as many participants are needed to obtain the same amount of data as would be required in a two-condition repeated measures design.

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Repeated measures design A repeated measures design consists of testing the same individuals on two or more conditions.

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Repeated measures design

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Repeated measures design strengths The key advantage of the repeated measures design is that individual differences between participants are removed as a potential confounding variable. Also the repeated measures design requires fewer participants, since data for all conditions derive from the same group of participants.

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Repeated measures design weaknesses The design also has its disadvantages. The range of potential uses is smaller than for the independent groups design. For example, it is not always possible to test the same participants twice.

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Repeated measures design weaknesses There is also a potential disadvantage resulting from order effects, although these order effects can be minimised. Order effects occur when people behave differently because of the order in which the conditions are performed.

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Repeated measures design weaknesses For example, the participant’s performance may be enhanced because of a practice effect, or performance may be reduced because of a boredom or fatigue effect.

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Repeated measures design weaknesses Order effects act as a confounding variable but can be reduced by using counterbalancing*. *Counterbalancing can be defined as using all of the possible orders of conditions to control order effects

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Repeated measures design weaknesses If there are two conditions in an experiment the first participant can do the first condition first and the second condition second. The second participant can do the second condition first and the first condition second and so on. Therefore any order effects should be randomised.

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Matched pairs design A matched pairs design consists of using different participants for each condition of the experiment but participant variables are controlled by matching pairs of variables on a key variable.

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Matched pairs design

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Matched pairs design In order to get the pairing precise enough, it is common to get one group of participants together and then look round for partners for everyone. Participants can be matched on variables which are considered to be relevant to the experiment in question.

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Matched pairs design For example, pairs of participants might be matched for their scores from intelligence or personality tests. Although this design combines the key benefits of both an independent and repeated measures design, achieving matched pairs of participants is a difficult and time consuming task which may be too costly to undertake.

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Matched pairs design Successful use of a matched pairs design is heavily dependent on the use of reliable and valid procedures for pre-testing participants to obtain matched pairs.

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Experimental design Look at the worksheet ‘Experimental design’ and decide which experimental design was used; and why the researcher might have used that design.

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Design flaws Now lets look at what happens if the design is flawed.

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Design flaws

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Design flaws It was finally discovered that Hans had become very adept at picking up subtle (and probably unintentional) movements on the part of the questioner that cued him as to when he should stop tapping his foot.

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Design flaws Suppose a questioner asked Hans to add 7 and 3. Hans would start tapping his hoof, and keep on tapping until the questioner stopped him by saying ‘‘Right! Ten!’’ or, more subtly, by moving slightly when the correct answer was reached.

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Design flaws You can see how important it is to ensure that extraneous cues or biases do not intrude into an experimental situation.

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Design flaws Look at the worksheet ‘Problems in design’, read the paragraph and answer the questions.

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Design flaws It is important, therefore, always to verify, using some external means, that the things you think are happening in your experiment are actually happening. Just because you leave the volume control on your amplifier at the same spot doesn’t mean the volume of a sound stimulus you are playing will be the same from day to day.

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Design flaws You should measure the output and not take the knob position for granted. Just because a frequency generator is set for 1000 Hz does not mean it is putting out a 1000 Hz signal. It is good science for you to measure the output frequency yourself.


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