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Research methods
Types of data
Nominal data: the value is a label for a category
Ordinal data: the value can be put in order or rank. Use measures of central tendency to
summarise or display the data
Interval data: the values have set intervals between them (eg. Temperature, height).

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Key details
Shows cause and effect (one thing changes, the other thing changes)
Independent variable (cause) and Dependent variable (effect)
Randomisation: used to decide the allocation of the participants into groups (eg. Coin toss)
Counterbalancing: used in repeated measures design to help overcome order effects. It's when half the…

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Reduces demand characteristics ­ may be unaware of study
Experimenter doesn't intervene directly in the research situation
Low control over IV since experimenter can't control directly
Reliability & Validity
Internal validity: establishes whether the IV was really caused by the results
External validity: effects can be generalised to different situation…

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Behaviours won't be missed
If lots of behaviours happen at once, it may be hard to collect everything

Covert and overt
Covert: participant is unaware of observation
High ecological validity
Low demand characteristics
Ethical issues (deception)
Overt: participant is aware of observation
Avoids ethical issues
High demand characteristics

Coding scheme…

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No IV or DV, only co-variables
Cannot conclude cause and effect
Hypotheses: must use correlation, not `difference'
Data could be collected from secondary source (MET office, data tables), through
questionnaires/self-reports or through observation studies
Presented in scatter graphs

Types of correlation
Positive: one variable increases, so does the other. Perfect…


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