Research Methods: revision notes

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  • Created on: 01-12-10 16:57
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Research Methods
Aims and Hypotheses
Aim: general purpose of an investigation, what you are trying to achieve in the
Hypothesis: a precise, testable statement or prediction about the expected outcome of an
Null Hypothesis: a prediction that states that results are due to chance and are not
significant in terms of supporting the idea being investigated. E.g. there is no evidence that
there is a difference between groups in the amount they remember.
Research Hypothesis: a prediction that states that results are not due to chance and that
they are significant in terms of supporting the idea being investigated. (E.g. there is evidence
that there is a difference between groups in the amount they remember).
One-tailed Hypothesis: is a directional hypothesis. E.g. instead of saying there will be a
difference between groups in the amount they remember, you predict which group will
remember the most.
Two-tailed Hypothesis: is one in which the direction of results is not predicted. E.g. you
may predict a difference between groups, but have no idea which ay the difference will fall.
Design Issues
Good design:
-The following factors are important to consider when designing an investigation.
A pilot study is test run on a few participants; this enables you to check for design
faults before carrying out an investigation on larger scale, this is a routine procedure.
Reliability of results is very important, so if a study is replicated the findings should be
Validity, does a test measure what it was designed to measure, for example, do IQ
tests really measure intelligence?
lnternal validity, extent to which study is free of design faults, which may affect
Ecological validity, a type of 'external validity'. This means the extent to which
generalisation can be made from the test environment to other situations.

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Repeated Measures: Testing the same group of people in different conditions, the
same people are used repeatedly.
Fewer people are needed.
Avoids the problem of participant variables
Order effects are more likely to occur
2. Independent groups: Testing separate groups of people - each group is tested in a
different condition (one of them being controlled).
Avoids order effect.…read more

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Counterbalancing: alternating the order in which participants perform in different
conditions of an experiment. E.g. group 1 does 'a' then `b'; group 2 does 'b' then 'a' to
eliminate order effects.
Randomisation: material for each condition in an experiment is presented in a
random order; this is also to prevent order effects.…read more

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Standardized instructions ­ each participant must be given exactly the same instructions,
ideally by the same person and in the same way. If some participants were given instructions,
which included demonstrations of how to do a task, and others were not, this could affect the
results. One way of ensuring standardization is to provide written instructions, which should be
simple and clear.
Ethical Issues
Ethics are the standards of behaviour that we use in our dealings with others.…read more

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Some people may be unable to give informed consent, such as children or those with special needs.
Nevertheless, they must be asked if they are willing to help you, but full consent must be gained
from whoever is responsible for that person, such as a parent or career. These people must be given
full information, just as if they were the participants, before being asked for their consent.…read more

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Systematic sampling: Chooses subjects in a systematic way, for example,
every 10th person from a list or register.
To being with, all population is involved; this is an improvement of opportunity and volunteer sampling.
Not everyone has an equal chance of taking part so unrepresentative
Still possible to get a biased sample
6.…read more

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Concurrent validity: This involves comparing a new test with an already established
test designed to measure the same thing. If scores are similar, then the new test is
3. Predictive validity: This involves checking validity by seeing if future behaviour is
consistent with what we could predict based on our test, for example, if someone is
diagnosed a schizophrenic we would expect them to goon to show further
symptoms of this diagnosis.…read more

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Ratio level of measurement
Ratio data provides us with the strongest and most precise method of measurement.
Ratio scales have a true zero, e.g. time in seconds and distance in cm. negative numbers
have no meaning.
Descriptive statistics
Quantitative research: gathers data in numerical form and is concerned with making
'scientific' measurements. Quantitative data analysis uses a barrage of inferential statistical
Qualitative research: gathers information that is not in numerical form, for example, diary
accounts, open-ended questionnaires, unstructured interviews and unstructured
observations.…read more

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Does not represent all scores
Range: difference between largest and smallest scores, quote biggest and smallest scores,
or take smallest from biggest score and quote this figure.
Easy to calculate
Use with ordinal, interval or ratio level data
Does not indicate how tightly/widely spread scores are
Standard deviation: average variation around the mean, larger value indicates wider spread,
relies on data with equal interval between points.…read more

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Type 1 error: the null hypothesis is wrongly rejected- the results are, in fact, due to chance factors
and not due to the manipulation of our variable. The reason for a type 1 error is that a too lenient
level of significance has been used (e.g. p0.01).
2. Type 2 errors: the null hypothesis is wrongly accepted ­ the results are in fact, due to the
manipulation of our variable and not due to chance factors.…read more


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