Research Methods

• What is primary data?

  Primary data refers to data that is collected firsthand by the researcher for a specific research purpose/investigation.
• Limitation of primary data?

  • Requires time and effort on part of the researcher to develop resources etc.
  • Costly, compared to easily accessible secondary data.
• How to improve validity of a questionnaire?

  • Identifying and removing any leading, ambiguous, overly complex or double-barrelled questions.
  • Compare the questionnaire to a successful one and note any differences.
  • Incorporate lie scale, so respondents are less aware of what is being tested.
• Strengths of random sampling

  Unbiased

  Confounding and extraneous variable should be equally divided
• Limitations of random sampling

  Time consuming, the list of target population may be difficult to obtain.

  Chances of being unrepresentative.

  Selected participants may refuse to take part.
• Strengths of systematic sampling

  Objective, researcher has no influence after system for selection has been established.
• Limitations of systematic sampling

  Time consuming

  Participants may refuse to take part.
• Strengths of stratified sampling

  Representative because its designed to accurately reflect the composition of the population.

  Able to generalise findings.
• Limitations of stratified sampling

  Identified strata cannot reflect all the ways people are different.
• Strengths of opportunity sampling

  Convenient, less costly of time and money as no need to divide population.
• Limitations of opportunity sampling

  Bias, unrepresentative of target population as its drawn from a very specific area.

  Findings cannot be generalised.

  Researcher bias, may not ask certain people.
• Strengths of volunteer sampling

  Minimal input from researcher, less time consuming.

  Researcher has participants who are more engaged.
• Limitations of volunteer sampling

  Volunteer bias, may attract certain profile of person.

  Affects how generalised findings can be.
• Strengths of structured observations

  Involve the use of behavioural categories to make the recording of data easier and more systematic.

  The data produced is likely numerical which means analysing and comparing behaviour is more straightforward.
• Limitations of structured observations

  Could be less detailed.

  Requires a sampling methods.
• Strengths of unstructured observations

  Greater richness and depth of detail in data collected.
• Limitations of unstructured observations

  Produce qualitative data that can be more difficult to record and analyse.

  Greater risk of observer bias as there are no objective behavioural categories.

  The researcher may only record behaviours that 'catch their eye' and they may not be the most important or useful.
• Strengths of event sampling

  Useful when the target behaviour or event occurs quite infrequently and could be missed if time sampling was used.
• Limitations of event sampling

  If specified event is too complex, the observer may overlook important details.
• Strengths of time sampling

  Effective in reducing number of observations that have to be made- observer fatigue reduced.
• Limitations of time sampling

  Instances where behaviour is sampled may be unrepresentative of the observation of a whole.
• Strengths of case studies

  Qualitative data that provides rich information about an individual or group, unique to them and their experiences.

  Holistic as it looks at the individual as a whole.

  Rarity means that it provides in depth information about cases uncommon to society.

  Insight into cases that we would not normally be able to construct ourselves due to BPS Ethical guidelines.
• Limitations of case studies

  Lacks scientific rigour and provides little basis for generalisation of results to wider population.

  Lacks objectivity as a subjective researcher may influence case study (researcher/observer bias).

  Difficult to replicate due to being individual cases.

  Time consuming to gather all the data from a persons life.
• What is a strong correlation?

  0.8 or above
• What is a weak correlation?

  Below 0.8
• Advantages of correlations

  Can be used when it would be unethical or impractical to manipulate variables and can make use of existing data.

  If correlation is significant then further research is justified.

  As with experiments the procedures can be repeated again which means findings can be confirmed.
• Disadvantages of correlations

  People often misinterpret correlations and assume a cause and effect has been found, whereas this is not possible.

  There may be other unknown variables (intervening variables) that can explain why the co-variables being studied are linked.

  As with experiments, may lack internal/external validity.
• How to improve internal validity

  Standardised procedures

  Control group as well as experimental groups to see if changes in the DV are caused by the IV

  Anonymity

  Single-blind procedure

  Double-blind procedure
• What can affect the internal validity of a study

  Investigator effects

  Demand characteristics

  Confounding variables

  Social desirability