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Statistical tests
Spearman-rank
Research aim = test for significant correlation
Participant design = correlation (NOT ---> independent, repeated or matched)
Level of measurement = ordinal or interval
Mann-Whitney U
Research aim test of significant difference for unrelated data
Participant design = independent measures
Level of measurement = ordinal or interval
Chi squared
Research aim = tests for significant difference
Participant design = independent measures
Levels of measurement = nominal
What to do before carrying out a statistical test:
1: determine the level of measurement... NOI
2: determine if the hypothesis is one tailed or two.
3: determine if this hypothesis is... a test of difference / a relationship / a correlation
4: choose a level of significance, for As ---> p < 0.05 or p < 0.01, so 1 in 20 and 1 in 100.
5: write out a null hypothesis.
6: carry out the appropriate test
7: find and use the relevant statistical table
8: check the results achieved, N or Df against the critical value.
9: for the test to be significant and the null hypothesis rejected...
Mann Whitney = value for U to be critical value
Spearman + chi = values to be critical value…read more

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Methodology PG1
Observational research method:
Features observation as the main way data is gathered, without setting up experiment or using scanning techniques or other research methods
Behaviour is observed but the aspects of the study and the IV is not manipulated. The IV e.g. gender may be present but naturally occurring
What seems like observational research but is not:
In lab experiments ­ you observe behaviour, but there are careful controls of sampling and group allocation. The IV is carefully manipulated
Case studies ­ they involve observation, but the research method itself is the case study so it is not an observational research method.
Types of observation:
Structured observation ­
Allows the situation to be repeated with different participants, the researcher is able to observe what happens, e.g. through a one-way mirror.
There is still no manipulation of the IV, but the setting and situation are manipulated. E.g. commonly used in child psychology.
Structured observations can be used to set up but not destroy naturally occurring interactions.
Naturalistic observation ­
They take place in the participants natural settings, with no manipulation by the researcher. There are two types of natural observation
(Participant observation) where observers are part of the situation and are playing as a participant.
(non-participant observation) where observers are not part of what is happening. The observers can then be covert or overt
Covert = the observation is kept secret from the participants
Overt = the participants know they are being observed and possibly why.
Tallying:
This involves making a mark every time a behaviour or whatever is being observed occurs
There needs to be an initial observation session so that they can know which behaviour they should tally.
Time sampling:
If tallying is carried out, there's one important problem which needs to be addressed ­ you need to know when to make a tally mark.
e.g. if you make a mark when a child plays with a certain toy, what if they continue with this toy for a long time.
This is when time tallying is used, where you can make a tally every minute (or any other chosen interval) the child is with the toy.…read more

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Methodology PG2
Non-participant observation:
STREGNHTS-
1: observer has no other role, can concentrate on observation --> more impartial and objective, record and take notes more efficiently
2: they can carry out time sampling and tallying more systematically.
WEAKNESSES-
1: lack validity, as what is recorded is not normal and the observer may be noticeable, which would affect the situation.
2: the observer my have insufficient understanding of what they are observing, meaning lower ability to record valid data.
Participant observations:
STRENGHTS-
1: observers do not disrupt what is happening, so ecological validity = greater, they do not affect the situation
2: observers may have more access to data so would obtain more data as the participant can offer more data through greater interactions.
WEAKNESSES-
1: observers may be so involved that they would not have time to record the observations, they also have other roles so cannot e.g. tally info
2: observers are part of the group so participant observations are hard to replicate making it difficult to check for reliability.
Covert observation:
STRENGHTS-
1: valid data collected as participants unaware, so more natural behaviour may occur.
2: observers can take notes without worry that participants will be aware that they are doing so, therefore more data can be collected.
WEAKNESSES-
1: unethical, no informed consent, BPS do not allow secret observations and distress may occur if participant discover they were observed.
2: hard to observe behaviour secretly, they need to be in a suitable position where they will not be discovered.
Overt observation:
STRENGHT-
1: more ethical, participant can be give informed consent and right to withdraw.
2: observer can ask for help to set up a suitable place for observation and in gathering data
WEAKNESSES-
1: low validity, participant may not act normally as they know they are being observed.
2: Participant observers find it difficult to carry out duties, those being observed would be aware that observers are taking on different roles…read more

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Naturalistic observations:
Methodology PG3
STRENGHTS-
1: The setting is real so there is ecological validity, the data is therefore real and the study gathers data that it claims to gather.
2: allot of data can be gathered in a naturalistic observation, with behaviour, emotions, language can all be observed and interpreted.
WEAKNESSES-
1: subjectivity could arise through some interpretation where the observers decide which categories to use and place certain behaviours.
2: lack generalizability, observations are at that moment in time from those specific situations making it hard to generalise to other situations
Structured observations:
STRENGHTS-
1: there are controls so cause and effect conclusions can be easily drawn.
2: there are also fewer factors to affect the conclusions, allowing for these to be tested for reliability as they are greatly controlled
WEAKNESSES-
1: lack validity, the structured nature makes situations artificial and data gathered often lacks ecological validity.
Laboratory experiment:
Description key points-
1: takes place in a controlled and artificial environment.
2: The IV is manipulated and the DV is measured to see the effect that manipulating the IV had.
3: The aim is a cause and effect relationship rather than a correlation.
4: procedures are scientific... experimental + control group used, EV are controlled preventing confounding variables, standardised
procedure
5: Sampling careful to prevent participant variables, controls precise to prevent situational variables, care taken to avoid experimenter effect.
6: in repeated measures design, counter balancing or randomisation used to prevent rehearsal and fatigue and order effects.
Evaluation key points-
STRENGHTS:
1: high level of control allows replication, this allows testing for reliability, for scientific data to be built up it must be reliable.
2: high generalizability, due to carful sampling techniques and controls. This allows the data to be used to predict outcomes
3: careful controls allows a cause and effect relationship to be established. So the manipulation of the IV caused the DV
4: objectivity is maintained through the high levels of controls
WEAKNESSES:
1: controls = lack in ecological validity, the situation is unlikely to represent real life, the results may therefore not be as generalizable.
2: lack credibility, the results may not be valid to the extent that the findings are not useful.
3: the carful operationalization of the IV and DV means they may be artificial, so nothing meaningful is measured.
4: demand characteristic may occur, participant give responses they think experimenters want = bias.…read more

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Methodology PG4
Ethical guideline for the use of human participants:
Fully informed consent: They should be told full aim of study, and what procedure will occur. Sometime not possible so, good debrief needed
Deception: Participants should not be deceived, however sometimes it may be necessary so they have to agree to do the test knowing that
they will not be told all the info
Right to withdraw: Free to leave any time, can take/ destroy their data. If paid for experiment, they still keep $
Competent: Researcher must have the necessary qualifications, if in doubt they must seek advice and help from someone who is competent.
Debrief: At end of study, fully tell them aim, offer time to ask any questions. Allows recording of experience
Confidentiality: all data should be confidential and participant not be identifiable, it is rare for real names to be used in case studies.
Privacy: the rights of individuals in respect to confidentiality and privacy should be respected.
Ethical arguments for use of animals:
Strengths
1: procedures can be carried out that cannot in humans, giving an advanced knowledge to our brains and genetics
2: in drug development animals are necessary to test if drug is safe, the knowledge from this can improve humans lives
Weaknesses
1: surgical procedures carried out, causes pain + discomfort for animals and some even die.
2: in lab experiments animals are confined in cages that do not represent their environment, some are even bred for experimentation.…read more

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