case studies, types of data, longitudinal + cross sectional studies

Quantitative data

data that can be measured numerically so that statistical analysis can be completed, e.g. scores on a test

Qualitative data

data that can be observed but not measured numerically

usually takes the form of words, thoughts and feelings

difficult to analyse

primary sources (data)

information (data) that is directly collated by the researcher first hand, e.g. collecting data through a questionnaire, experiment, interview for their research

secondary sources (data)

information (data) that has not been directly collected/created by the researcher e.g. literature review

was watson and raynor qualitative/quantitative and WHY?

Qualitative because they described how albert responded in response to stimuli, e.g. he ‘fell forward’

was watson and raynor primary or secondary data and why?

primary because it was a controlled observation conducted by themselves

was loftus and palmer quantitative/qualitative and WHY?

Quantitative because participants answered with an estimation of speed in miles per hour, which is a numerical value

was loftus and palmer primary or secondary and why?

primary as loftus and palmer collated the data themselves

was raine et al qualitative/quantitative and why?

qualitative as they described the area of the brain and the activity, e.g. they found ‘increased activity in the occipital lobe’ in murderers

give 2 strengths of quantitative data

easier to collect information from a large number of participants, data easier to analyse

give 2 weaknesses of quantitative data

tends to lose the ‘human’ element of behaviour, offers shallow view of behaviour

give 2 strengths of qualitative data

can offer a more individualised ‘human’ view of behaviour, provides in depth detailed data

2 weaknesses of qualitative data

can be difficult to analyse, data tends to come from a limited number/range of people

what is a longitudinal study?

• conducting research over a long period of time, same participants

• observe long term effects of X on a specific behaviour

• use other methodologies like case studies, interviews etc.

• participants commonly assessed on two or more occasions as they get older.

• allows the researcher to see long-term effects e.g. how memory gradually decreases with age

what is a cross sectional study

• comparing one group of participants, representing a cross section of society, against another at the same point in time.

• one group of participants representing one section of society e.g. young people are compared with participants from another group e.g. old people

4 things to evaluate cross sectional/longitudinal studies

participant variables, attrition, cohort effect, demand characteristics

what are participant variables

characteristic/aspect of a participant’s background that might influence the outcome of a study e.g age

what is attrition

where some participants inevitably drop out over the course of a study. those who drop our are more likely to have particular characteristics e.g. less motivated, more unhappy, done less well)

what is the cohort effect?

occurs because a group/cohort of people who are all the same age share certain experiences, e.g. children born just before WW1 had poor diets in infancy because of rationing. in a longitudinal study, findings that only consider 1 cohort may not be generalisable due to its unique characteristics

2 strengths of longitudinal studies?

• same person is tested numerous times so participant variables controlled

• developmental trends spotted easier

3 weaknesses of longitudinal studies

• high attrition rates which may lead to a biased smaller sample,

• cohort effects

• participants more likely to be aware of aims (demand characteristics)

2 strengths of cross sectional studies

• relatively quick/cheap in comparison- no follow up necessary

• easier to obtain participants as less pressure for them to take part

2 weaknesses of cross-sectional

participant variables- may not be clear why there are differences between 2 cohorts. just a snapshot- harder to identify and analyse trends