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Cheat sheet
Read claims about the mind: cheat sheet
The summary, key terms and the trap to avoid for every lesson, in order. Print it, or read it, cover it, and say it back.
- A correlation shows two things change together; it doesn't show one causes the other.
- Check three other explanations: a third factor, reverse direction, chance.
- Chocolate and Nobel prizes: a strong link, most likely explained by a third factor such as national wealth.
- "Linked to" and "associated with" mean what they say: a link, not a cause.
- Showing cause usually needs an experiment.
- correlation
- a link where two things tend to change together
- positive correlation
- both tend to be high together, or low together
- negative correlation
- when one is higher, the other tends to be lower
- r (correlation coefficient)
- a number from −1 to +1 showing how strong a correlation is
- confounding variable
- a third factor that affects both things and creates a link between them
- reverse causation
- the effect actually causing the supposed cause
- illusory correlation
- a link people believe in that the evidence doesn't show
Watch out: Treating "linked to", "associated with" and "tied to" as if they meant "causes". They are the words researchers use precisely because the study can't show cause. When you see them, read them literally.
- An experiment changes one thing (independent variable) and measures another (dependent variable).
- Random assignment makes the groups alike, so a difference can be put down to the change.
- A placebo makes expectations equal; double-blinding stops anyone's hopes shaping the results.
- Surveys and observational studies show links, not cause.
- Some questions can't be tested by experiment; then the evidence is less certain.
- experiment
- a study that changes one thing on purpose and measures the effect
- independent variable
- what the researcher changes
- dependent variable
- what the researcher measures
- control group
- the group that doesn't get the change, used for comparison
- random assignment
- using chance to decide who goes in each group
- placebo
- a fake treatment that looks like the real one
- double-blind
- neither the participants nor the researchers who run and score the study know who is in which group
- observational study
- a study that measures what happens without changing anything
Watch out: Calling any study an "experiment". Many headlines describe surveys or observational studies, where researchers only watch and measure. They can find links but not prove cause. Ask: did the researchers decide who got what, by chance? If not, it isn't an experiment in this sense.
- Check who was studied and how many: small or self-selected samples mislead.
- "Statistically significant" means the result would be unlikely if there were no real effect; it doesn't mean big or important.
- A p-value is not the chance a finding is true.
- Effect size shows how big a result is; Cohen's rough guide is 0.2 small, 0.5 medium, 0.8 large.
- Small studies produce more dramatic results, and more that don't hold up.
- sample
- the people (or things) studied
- self-selected sample
- a sample of people who chose to take part, such as an online poll
- statistically significant
- a result that would be unlikely if there were no real effect, usually p below 0.05
- p-value
- how often results at least this strong would appear if there were no real effect
- effect size
- how big a difference or link is
- Cohen's d
- an effect size measuring a difference in standard deviations: about 0.2 small, 0.5 medium, 0.8 large
Watch out: Reading "significant" in its everyday sense, meaning "big" or "important". In research it is a technical word about chance, not size. Always look for the effect size, or the actual numbers, next to it.
- Replication means repeating a study to see if the result holds.
- In 2015, only 36% of 100 repeated psychology studies found a significant result again (97% of originals had), with effects about half as big.
- Publication bias, p-hacking and small samples produced many false findings.
- Ego depletion and power posing's effects on hormones and risk-taking did not hold up; testing yourself and anchoring did.
- Reforms: preregistration, registered reports, bigger samples, open data, multi-lab repeats.
- replication
- repeating a study with new participants to see if the result holds
- replication crisis
- the discovery, around 2011–2015, that many published findings failed to replicate
- publication bias
- exciting, significant results being more likely to be published than null results
- p-hacking
- trying different analyses or data choices until a result becomes significant
- preregistration
- publishing a study's plan and analysis before collecting data
- registered report
- a study accepted for publication on its plan, before the results are known
Watch out: Swinging from "a study proves it" to "psychology is all rubbish". Replication failures were more common in small, surprising studies. Large, repeated findings, such as the benefits of testing yourself and spacing your study, have held up again and again. The skill is telling them apart, not trusting or dismissing everything.
- Learning styles: teaching to a preferred style doesn't improve learning; match the method to the material.
- The 10% myth: the whole brain is active and used.
- Left- and right-brained people: tasks specialise, people don't.
- The Mozart effect: a brief result in college students that grew into a myth.
- Venting anger can increase it.
- Myths spread because they're simple and have a grain of truth; check the evidence, not the vocabulary.
- learning styles
- the idea that people learn best when taught in their preferred mode; not supported by evidence
- hemispheric specialisation
- the real finding that some tasks rely more on one side of the brain
- Mozart effect
- a claimed boost to intelligence from listening to Mozart; the evidence is weak
- catharsis
- the idea that venting anger releases it; experiments suggest it can increase anger
Watch out: Believing a claim because it comes with brain pictures or scientific words. In one study (Weisberg and colleagues, 2008), adding irrelevant neuroscience jargon made poor explanations seem more satisfying to non-experts. (Whether brain pictures alone have the same pull is less clear: later studies found little effect.) Judge the evidence, not the vocabulary.