Psychology research might seem complex, but it's actually quite straightforward... Show more
Other66 views·Updated May 7, 2026·2 pagesUnderstanding Psychology Research Methods
E
Eliza Haigh@elizahaigh_ngxf
1
of 2
Research Basics and Sampling Methods
Extraneous variables are sneaky factors that can mess up your experiment results without you realising it. They affect what you're measuring (the dependent variable) but aren't part of your actual experiment design.
There are different types to watch out for: participant variables (differences between people), situational variables like demand characteristics (when participants guess what you want them to do), and order effects (when doing tasks in a certain sequence affects performance).
Sampling methods help you choose who takes part in your study. Random sampling gives everyone an equal chance of being selected, creating a representative group. Stratified sampling ensures you get proportional representation from different groups in your target population. Volunteer sampling involves putting up adverts and letting people come forward - though this can lead to researcher bias since you're choosing from whoever responds.
Top Tip: Remember that good sampling reduces bias and makes your results more reliable!
2
of 2
Experimental Design and Hypotheses
Laboratory experiments are the gold standard in psychology research. You manipulate the independent variable (what you change), measure the dependent variable (what you're studying), and control everything else in a laboratory setting to discover cause and effect relationships.
Experimental designs come in three main types. Independent measures uses two separate groups - one does condition A, the other does condition B. Repeated measures uses the same group for both conditions. Matched pairs involves pairing up participants based on similar characteristics, then splitting the pairs between conditions.
Your hypothesis needs to be testable and measurable. A directional hypothesis predicts which way results will go, whilst a non-directional hypothesis just predicts there will be a difference. Don't forget your null hypothesis - this states there will be no effect between your variables.
Remember: All variables must be operationalised - written in a way that can actually be tested and measured!
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Other66 views·Updated May 7, 2026·2 pagesUnderstanding Psychology Research Methods
E
Eliza Haigh@elizahaigh_ngxf
Psychology research might seem complex, but it's actually quite straightforward once you understand the basic building blocks. These fundamentals will help you design proper experiments and understand how psychologists gather reliable data about human behaviour.
1
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Research Basics and Sampling Methods
Extraneous variables are sneaky factors that can mess up your experiment results without you realising it. They affect what you're measuring (the dependent variable) but aren't part of your actual experiment design.
There are different types to watch out for: participant variables (differences between people), situational variables like demand characteristics (when participants guess what you want them to do), and order effects (when doing tasks in a certain sequence affects performance).
Sampling methods help you choose who takes part in your study. Random sampling gives everyone an equal chance of being selected, creating a representative group. Stratified sampling ensures you get proportional representation from different groups in your target population. Volunteer sampling involves putting up adverts and letting people come forward - though this can lead to researcher bias since you're choosing from whoever responds.
Top Tip: Remember that good sampling reduces bias and makes your results more reliable!
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of 2Sign up to see the content. It's free!
- Access to all documents
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Experimental Design and Hypotheses
Laboratory experiments are the gold standard in psychology research. You manipulate the independent variable (what you change), measure the dependent variable (what you're studying), and control everything else in a laboratory setting to discover cause and effect relationships.
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Your hypothesis needs to be testable and measurable. A directional hypothesis predicts which way results will go, whilst a non-directional hypothesis just predicts there will be a difference. Don't forget your null hypothesis - this states there will be no effect between your variables.
Remember: All variables must be operationalised - written in a way that can actually be tested and measured!
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