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

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University Course Reader · STEM

Because nobody was assigned anything, the paper was an observational study, and the authors wrote linked to rather than caused.

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Overview

An observational study and an experiment are the two ways research gets done, and one question splits them: did the researchers change anything? In an experiment they change one thing on purpose, for example giving a treatment to a randomly chosen half of 200 volunteers and comparing the halves. In an observational study they change nothing and only record what was already happening. Watching can show that two things go together. Assigning can settle whether one causes the other, or does not.
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Overview

An observational study is science with its hands in its pockets: not a thing touched, everything noted. An experiment reaches in, flips one switch, and sees what follows. The gap between them decides what a study is allowed to claim. Note that the 500 drivers who choose the back road clock faster commutes, and you have learned that back-road drivers are quick, maybe. Send 500 randomly picked drivers down it and time everyone, and now the road itself is on trial. Noting earns linked. Rearranging earns caused. Worth checking which one you are being sold. 😎

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Detail

An observational study and an experiment are the two kinds of study, split by whether the researchers changed anything. In an experiment they assign something; in an observational study they only record. An app company wants to know whether its new home screen keeps people around. The observational version needs no setup: the company's records already show what users did on their own. The 2,000 who switched the screen on early open the app 9 nights in 10; everyone else opens it 5 in 10. That can claim the two go together, and no more: early switchers were the keenest users to begin with. A home screen, though, is a thing the company can assign, so it runs the experiment: 5,000 users picked by chance get the new screen, 5,000 keep the old, and the groups start out alike. Whatever gap opens now, large, small, or none at all, is the screen's true effect. Some things cannot be studied this way: no one can assign a different childhood, and no one should assign a harm. For those, an observational study is the only one possible, often following the same people for a decade or more. So ask one question of any study: did they change anything, or just watch? When a headline says linked to or associated with, the researchers were almost certainly watching, and watching alone supports linked, not causes.
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Detail

An observational study writes down life as found. An experiment rearranges one piece of it on purpose. Some topics only allow one of the two, and piano is a good example. A district notices its 300 piano kids average 8 points higher in maths. To settle if lessons cause the points, the experiment would have to pick families at random, order half into two years of lessons, forbid the rest, and compare scores after. No parent signs that form, so the experiment is off the table for good. Watching is the one that can actually happen: same kids, real scores, nothing faked, and it is honest work. What it cannot do is promise the piano did it. Piano families were already different before the first lesson, with more spare money, fuller calendars, and a quiet room to practice in, and any of that could be moving the maths scores. So the finding ships as linked to, and linked to is the truth, not a failure. Caused it would need the study no parent allows. Which is why the wording of a claim quietly tells you which of the two studies actually happened. 😎

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Analogy

On a long street, the houses with solar panels pay about $30 a month less for electricity. That is an observational study: nobody arranged anything; the panels and the bills were already there to be counted. It can claim the two go together, but panel owners also chose sunnier roofs and richer budgets, so the bills settle nothing. Then the utility runs an experiment, because panels are a thing it can assign: a free-install pilot, one house in every two picked by coin flip. Now the two sets of houses start out alike, sunny and shaded mixed evenly, and whatever the panelled half saves from here on belongs to the panels. Same street, same panels. What changed is who decided, and that decides what the numbers can claim.
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Analogy

A productivity account tells its 40,000 followers that early risers earn more. Ask what was actually done: no one touched anyone's alarm, the account surveyed people who were up at 5am anyway and compared their salaries to everyone else's. That makes it an observational study, and observational is all it can ever be, because no app on earth gets to hand 200 strangers a bedtime. An experiment would need exactly that, forced 5am for some and a lie-in for the rest, with salaries compared a year later. Since that study cannot exist, the honest headline stops at early rising and higher salaries come as a package. Wake at 5am and get rich is the experiment no one ran. 😎
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Formal definition — The same term, explained the usual way

An experimental study is one in which investigators assign an exposure or intervention to some units and not others, typically by randomization, and compare subsequent outcomes; assignment under the investigators' control is what licenses causal interpretation of differences between groups. An observational study is one in which no exposure is assigned: investigators record exposures and outcomes as they occur, so groups may differ systematically before the comparison begins, and associations require further evidence before causal claims are made. The designs answer different questions. Experiments are preferred where assignment is feasible and ethical, while observational designs permit study of exposures that cannot or should not be assigned, and of large populations over long periods.

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