Research methods flashcards

Research methods in IB Psychology covers how psychologists design studies, collect data, and draw conclusions. Students must understand the difference between qualitative and quantitative approaches, and be familiar with experimental, correlational, and non-experimental methods such as case studies, interviews, and observations. Key concepts include independent and dependent variables, operationalisation, sampling techniques, and ethical considerations including informed consent and confidentiality. Students should be able to evaluate research in terms of reliability, validity, and generalisability, and understand how researcher bias and demand characteristics can threaten the credibility of findings. Understanding the distinction between correlation and causation is essential, as is knowing how triangulation and replication strengthen research. Both inductive and deductive reasoning underpin different methodological approaches, and students must be able to apply these ideas critically when discussing psychological studies.

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 the outcome measured to see if it changed as a result.

2. Card 2

   What does it mean to operationalise a variable?

   Operationalisation means defining a variable in a precise, measurable way so it can be consistently tested, e.g. measuring anxiety by heart rate.

3. Card 3

   What is the difference between reliability and validity in research?

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

4. Card 4

   Why does correlation not imply causation?

   A correlation shows a relationship between two variables but cannot confirm one causes the other, as a third variable may explain both.

5. Card 5

   What is a confounding variable?

   A confounding variable is an uncontrolled factor that varies alongside the independent variable and may offer an alternative explanation for results.

6. Card 6

   What is the difference between a random sample and an opportunity sample?

   A random sample gives every member of a population an equal chance of selection; an opportunity sample uses whoever is conveniently available.

7. Card 7

   What are demand characteristics and why do they matter?

   Demand characteristics occur when participants guess the study's aim and alter their behaviour, reducing the internal validity of findings.

8. Card 8

   What is the difference between qualitative and quantitative data?

   Quantitative data is numerical and measurable; qualitative data is descriptive, capturing meaning, experience, and depth of understanding.

9. Card 9

   What is triangulation and why is it used?

   Triangulation involves using multiple methods, sources, or researchers to cross-check findings, increasing the credibility and validity of conclusions.

10. Card 10

    What ethical principle requires participants to agree to take part with full knowledge of the study?

    Informed consent requires participants to be told enough about the study to make a voluntary, knowledgeable decision about whether to participate.

11. Card 11

    What is researcher bias and how can it affect a study?

    Researcher bias occurs when a researcher's expectations influence data collection or interpretation, potentially distorting the findings of a study.

12. Card 12

    What is the purpose of a control condition in an experiment?

    A control condition provides a baseline by exposing participants to no manipulation, allowing comparison with the experimental condition.

• Many students confuse reliability with validity, incorrectly assuming that if a study produces consistent results it must also be measuring the right thing.
• Students often claim that a correlational study proves causation, forgetting that a third variable or reverse causation could equally explain the relationship.
• A common exam error is describing an opportunity sample as biased without explaining why this limits generalisability to the broader target population.

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