Research & Statistics Terms, Explained

News stories about studies rarely explain what the study actually showed. This section covers the vocabulary of research itself, including what a p-value means, what a control group is for, and why two studies can disagree without either of them being wrong. Inside a paper, the Clicked extension does the same job — a research paper assistant that explains any term you highlight, in place. These pages explain how research works, and are not medical or scientific advice.

All 31 terms

What is a Confidence Interval?

The range a study reports around its result, and why a wide one means nobody knows yet.

😎 Slang inside

What is a Control Group?

The group that gets nothing, and why a study without one proves almost nothing.

😎 Slang inside

Correlation vs. Causation: What's the Difference?

Two things moving together is not one causing the other, and the gap is where bad headlines live.

😎 Slang inside

What is a p-value?

How easily luck alone could fake a result — and what 0.05 actually means.

😎 Slang inside

What is Peer Review?

Who checks a study before publication, what that catches, and what it does not.

😎 Slang inside

How to actually read a research paper

Skim smart, break the jargon wall, and keep what you learned — one session, done right.

Guide

What is Sample Size?

How many were actually studied, why small numbers mislead, and why big ones are not automatically better.

😎 Slang inside

What is Standard Deviation?

How far the numbers wander from their average — the spread two identical averages can hide.

😎 Slang inside

What does statistically significant mean?

It means probably not luck. It does not mean big, useful, or true.

😎 Slang inside

What is a double-blind study?

A trial where neither the participants nor the researchers know who got the real treatment, so nobody's expectations can shape the result.

😎 Slang inside

What is a meta-analysis?

Many small studies merged into one answer, and why the merge can still mislead.

😎 Slang inside

What is a preprint?

A research paper posted publicly before peer review. Fast, free to read, and not yet checked.

😎 Slang inside

What is a randomized controlled trial (RCT)?

Chance picks who gets the pill, so the pill explains the result.

😎 Slang inside

What is effect size?

How big a difference actually is, separate from whether it's real. The number news stories skip.

😎 Slang inside

What is regression to the mean?

An extreme result is usually followed by an ordinary one, and something else takes the credit.

😎 Slang inside

What is selection bias?

When how you picked your sample decides the answer before the study starts. Big samples don't fix it.

😎 Slang inside

What is survivorship bias?

Judging by the winners because the losers aren't around to be counted. The most common way data lies.

😎 Slang inside

What is the placebo effect?

The pill is sugar and the relief is real, which is why every drug has to beat it.

😎 Slang inside

What is the Null Hypothesis?

The "nothing is going on" claim every study has to beat, and why beating it proves less than you think.

😎 Slang inside

What are False Positives and False Negatives?

The two ways a test can be wrong, why fixing one makes the other worse, and how to choose.

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What is a Confounding Variable?

The hidden third factor that makes two unrelated things look like cause and effect.

😎 Slang inside

What is Publication Bias?

Why the studies that found nothing never get published, and what that does to everything you read.

😎 Slang inside

What is a Funnel Plot?

The chart that shows when studies are missing from the record, and why it is not the sales funnel.

😎 Slang inside

What is Anecdotal Evidence?

Why one person's story is not proof, why it feels like proof anyway, and what it is actually good for.

😎 Slang inside

What is an Outlier?

The one number far from the rest, how it bends the average, and the three things it can turn out to be.

😎 Slang inside

What is a Forest Plot?

Each study gets a row and a range. A range crossing the no-difference line means that study alone could not tell. The diamond at the foot is what they say together.

😎 Slang inside

What is P-Hacking?

Nothing is faked and every number is real. The analysis was simply chosen after seeing the answers, from many quiet tries, and only the winning version was reported.

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What's the Difference Between an Odds Ratio and a Relative Risk?

A relative risk of 2 means twice as likely. An odds ratio of 2 means something close to that only when the outcome is rare, and headlines skip the difference.

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What's the Difference Between Absolute Risk and Relative Risk?

A percentage change compares two chances without showing you either one. The same 50% rise fits 2 in a million and 2 in 10. Ask for the counts.

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What's the Difference Between Sensitivity and Specificity?

A yes-or-no test has two scores: the share of real cases it catches, and the share of non-cases it leaves alone. One number alone can hide a useless test.

😎 Slang inside

What's the Difference Between an Observational Study and an Experiment?

Every study is one of two kinds: researchers assigned something, or they only watched. The kind decides whether a finding can say causes or only linked.

😎 Slang inside