Research methods flashcards

Research methods is a core topic in A-Level Psychology covering how psychologists design and conduct studies to investigate behaviour. Students must understand different research designs, including experiments, observations, questionnaires, interviews, and case studies, along with their strengths and limitations. Key concepts include variables, sampling techniques, ethical guidelines, and the difference between qualitative and quantitative data. Students also need to understand reliability and validity, how to analyse data using descriptive and inferential statistics, and how to interpret graphs and tables. The distinction between hypotheses (directional and non-directional), levels of measurement, and the logic of significance testing are all essential. Understanding how to evaluate research in terms of its scientific credibility, generalisability, and ethical integrity is central to performing well in this area.

1. Card 1

   What is the difference between an independent variable and a dependent variable?

   The independent variable is manipulated by the researcher; the dependent variable is what is measured to see the effect of that manipulation.

2. Card 2

   What is operationalisation in psychological research?

   Operationalisation means defining variables in a precise, measurable way so they can be consistently tested, e.g. measuring anxiety as score on a rating scale.

3. Card 3

   What is the difference between reliability and validity?

   Reliability refers to consistency of measurement; validity refers to whether a study actually measures what it claims to measure.

4. Card 4

   What is a confounding variable?

   A confounding variable is an uncontrolled variable that varies alongside the IV, making it unclear whether it, rather than the IV, caused changes in the DV.

5. Card 5

   What is the difference between a directional and a non-directional hypothesis?

   A directional hypothesis predicts the specific nature of an effect; a non-directional hypothesis predicts a difference or relationship without specifying its direction.

6. Card 6

   What are the three main experimental designs and their key trade-off?

   Repeated measures, independent groups, and matched pairs each balance controlling participant variables against avoiding order effects or demand characteristics.

7. Card 7

   What is the difference between random sampling and opportunity sampling?

   Random sampling gives every member of the target population an equal chance of selection; opportunity sampling uses whoever is conveniently available.

8. Card 8

   What does inter-rater reliability mean?

   Inter-rater reliability is the degree of agreement between two or more observers coding the same behaviour, usually measured by a correlation coefficient.

9. Card 9

   What is the difference between qualitative and quantitative data?

   Quantitative data is numerical and allows statistical analysis; qualitative data is descriptive, capturing meaning and experience in words or themes.

10. Card 10

    What does a p-value of p < 0.05 mean in psychology?

    It means there is less than a 5% probability the results occurred by chance, so the researcher rejects the null hypothesis at the standard significance level.

11. Card 11

    What is a Type I error and a Type II error in hypothesis testing?

    A Type I error is falsely rejecting a true null hypothesis; a Type II error is failing to reject a false null hypothesis, i.e. missing a real effect.

12. Card 12

    What are the British Psychological Society's key ethical principles for research?

    Core principles include informed consent, debriefing, the right to withdraw, confidentiality, and protection of participants from harm.

• Many students confuse reliability with validity, incorrectly using them interchangeably when they refer to distinct qualities of a measure.
• Students often state that a correlation shows causation, when in fact a correlational study can only demonstrate a relationship between two variables, not that one causes the other.
• A common error is describing all uncontrolled variables as confounding variables, when a confounding variable specifically must vary systematically with the independent variable to threaten the study's internal validity.

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