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Why are some kids sad?

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What makes the wind blow?

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How do birds fly?

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Our world is full of curious phenomena.

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To find answers or solve problems,

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we can use a process,

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which was first acknowledged

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by the scientist and philosopher

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Ibn al-Haytham in the 11th century.

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Also known as al-Hazn,

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he is considered to be the father of optics

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and the scientific method.

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There are six steps to it.

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1. Observe and ask questions.

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2. Research.

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3. Formulate a hypothesis.

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4. Test your hypothesis.

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5. Conclude.

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6. Share results.

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The goal of the scientific method

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is to find out the truth.

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Let's try.

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Step 1. Observe and question.

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Observation helps us formulate

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challenging questions

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that you will be able to test.

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A good question converts

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the natural sense of wonder

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into a focused line of investigation.

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When is the best time to drive to school?

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Which food is my dog's favorite?

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For example, if you observe

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that women smile more often than men,

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you might ask,

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why do women smile more often?

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Step 2. Research.

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Find out if other people have asked

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the same or similar questions.

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If you research online,

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use search terms like study, research,

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or meta-analysis,

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which is a summary of research

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for a specific topic.

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Read as much as you can

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about your particular subject

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to see what you can find out about.

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For example, research happiness

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based on gender

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or study the science of smiling

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in different cultural contexts.

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Step 3. Formulate a hypothesis.

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A hypothesis is a theory

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that you can test

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to see if your prediction

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is right or wrong.

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From your observation,

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you have noticed

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that women smile more often

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and that people who are smiling

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seem to be happy.

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From your research,

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you know that there are

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different types of smiles,

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shy, genuine, and false.

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In one paper,

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you read that baby girls

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smile more often than baby boys.

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Here is a hypothesis.

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Women smile more than men

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because they are happier than men.

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Step 4. Test your hypothesis.

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When you test your hypothesis,

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you want to make sure

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to do this in a fair way

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and that the conditions are constant.

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For this hypothesis,

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we can design a test

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where an interviewer

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talks with a set of men and women

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for five minutes each,

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counts how many times they smile,

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and then asks each one

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to rate their level of happiness.

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To get a good sample

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of the population,

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we invite 300 women

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and 300 men.

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Seems like a good test, right?

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But wait,

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what if the interviewer is a woman

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and men tend to smile more at women?

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Or vice versa?

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Or what if the topic discussed

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is one that interests women

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more than men?

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And what if people

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aren't reliable reporters

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of their actual level of happiness?

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So, clearly,

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we would need to be much more careful.

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Step 5. Analyze and conclude.

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Let's assume

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that you designed

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a very careful experiment,

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controlling for as many variables

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as possible.

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Now you can analyze the data

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to see if your hypothesis

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is correct or incorrect.

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Depending on your findings,

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you may want to change

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your hypothesis

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or change the design

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of your testing.

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Perhaps you have discovered

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an even more interesting question.

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This stage of the scientific method

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can be repeated

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as many times as necessary

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until you find

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just the right hypothesis

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and test method

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to find accurate results.

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Step 6. Share the results.

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When you are satisfied

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that you have proven

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or disproven

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something important,

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report your results.

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In science,

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it is important

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to detail your methods

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so that your peers

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can review your work,

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which is a critical step

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to getting published.

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If your results are solid,

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your experiment can be repeated

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by other scientists.

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Such reproducibility

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is a sign of good scientific work.

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But failed results

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can also be interesting.

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An incorrect prediction

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could prove to be important

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and should always be reported.

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To make sure

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you get it completely right,

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here are three more things

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you can check

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before you publish.

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A. Any scientific theory

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is falsifiable.

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Real scientists know

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that there is no such thing

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as a scientific proof.

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In other words,

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you can never prove

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your theory to be

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100% right.

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All you can do

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is find a lot

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of supporting evidence

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that it could be correct.

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Here is one example.

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Say that someone says,

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Hamsters can fly.

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We cannot prove

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that this is false.

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Yes, we have never seen

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a hamster fly,

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but we can't test

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all possible conditions

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or look in all possible places

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on the planet

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to know that all hamsters

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never fly.

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Maybe a space hamster does.

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So, while we can often prove

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that a phenomenon exists,

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it's much harder to prove

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the non-existence of something.

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If your theory can't possibly

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be proven wrong,

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then it's not falsifiable

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and hence not scientific.

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When you analyze your results,

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it is important to separate

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between two possible reasons,

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correlation or causation.

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Let's say you hear

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that towns that have more churches

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also have more bars.

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Could it be that religion

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makes people want to drink,

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or that drinking helps people

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to find God?

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If you add more facts,

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such as larger towns

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have both more bars

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and more churches,

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you can see that

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a larger population

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is a more likely cause

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of higher numbers

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of bars and churches.

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There is probably a correlation,

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but no causation.

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If we compare men with women

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and would conclude

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that women smile more

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and are more happy,

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then this still doesn't mean

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that it's happiness

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that makes them smile.

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Maybe they just eat

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more chocolate and cookies,

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which makes them both happy

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and smile a lot.

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When you publish,

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you've got to show

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all relevant facts.

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Colgate once ran

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an advertising campaign

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claiming that 80% of dentists

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recommend Colgate.

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What they didn't tell us

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is that when they asked

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dentists to select

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their preferred toothpaste,

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Colgate was just one

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of many other brands

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they also recommended.

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Colgate was later sued

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and forced to take down

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their misleading ads.

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The purpose of science

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is always to find out

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the truth and nothing

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but the truth.

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To use science to mislead us

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is wrong and terrible

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business practice.

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Let's do a last example together.

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I have two coins.

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One is bigger.

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Why?

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The small coin says 1 cent,

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the bigger one says 5.

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Aha!

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Small coins are worth

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less money.

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Bigger coins are worth

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more money.

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I pull some more coins

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from my pocket.

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Two more pennies,

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one more nickel,

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and a quarter dollar,

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which is 25 cents.

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Great!

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My hypothesis seems true.

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But wait.

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Is the quarter worth more

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because it is bigger?

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So is that a correlation

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or a causation?

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Hmm.

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My sample size is pretty small.

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I don't think I am ready

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to report my results.

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Can you help out?

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Please apply the scientific method

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to study your local currency.

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Maybe you have a hypothesis

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that we can test

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until we get solid,

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repeatable results to report.

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Please publish your findings

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in the comments below.

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Thanks for watching!