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- [Voiceover] Now run the experiment,

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and observe what happens.

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When you run the experiment

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here comes your truth or a falsehood.

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You'll either uphold your
prediction saying it was true.

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It worked, or you realize

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that your prediction was incorrect.

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That either the experiment had a flaw.

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Something didn't work, or simply,

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your hypothesis was not upheld.

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Your hypothesis was not valid.

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But to make this work,

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the experiment has to be
very carefully planned.

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In controlled experiments, you account

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for every variable except for one.

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If we go back to the
example of taking a drug,

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an Ibuprofen, Tylenol,
whatever you're taking.

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Pick one drug, and one drug's important.

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Not many, just one.

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Then okay, you take the drug.

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Do you take it with water?

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Do you take it with juice?

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Is it with a full
stomach, an empty stomach?

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Those are variables to think about.

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Do you take it before you go to sleep,

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when you wake up in the morning?

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Other variables are also age.

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Variables can be gender.

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Variables can be how long the
individual had a fever for.

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Variables can be how high the fever is.

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So all these are variables
that you need to try

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to account for to try to keep
it as uniform as possible

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and even then, you still wanna think about

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using a placebo or a false treatment,

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because the mind is a very powerful tool.

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A lot of times if someone takes a drug

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that drug might not actually help them,

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but because they think it
should help, it will help them.

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It's called the placebo effect.

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So what happens a lot
of times in experiments,

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in controlled experiments,
one group of individuals

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or one group of items is
given this false treatment.

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Probably one of the easiest
ways to think about this

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is a sugar pill.

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In clinical trials, a group of individuals

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is still given a pill, but
their pill is just pure sugar.

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There's no drug in it.

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Nothing can actually,
physically, chemically change

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what's going on, so this
placebo, it's looking at

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does the person get
better just by thinking

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they should get better?

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So it's your placebo effect.

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Well once that's done, once
you've run your experiment,

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if it held up the hypothesis,
if it was true, great.

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You're good to go, but
that very rarely happens

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in the first time.

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Usually what happens is
you modify the hypothesis.

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You go back and repeat.

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You make up a new experiment
and that new prediction,

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and you go through and test everything.

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You keep repeating until
your results are held up

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as a truth.

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Until your hypothesis and prediction

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are not shown to be false.

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This might be repeated once or twice.

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You might repeat this dozens of times.

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If you're thinking hold on.

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You said earlier that we
use the scientific method

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to figure what clothes to put on.

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I knew what clothes to put
on the very first time,

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and I didn't have to repeat any process.

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True, but was that the
first time you ever decided

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to put clothes on and go outside?

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No, I bet not.

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Probably when you were a child

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and your parents first allowed
you to pick your own clothes,

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I don't know if every single
time you picked the right way.

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Maybe you really, really,
really wanted to wear shorts

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in the middle of winter.

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Well what happens then?

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You walk outside.

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You realize you're cold.

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You either do one of two things.

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You deal with it because
you don't wanna show

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that you're cold, could be stubborn.

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Or you go back in the house
realizing you're cold.

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You failed the experiment
because you are cold,

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so you go back and change the clothing

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to put warmer clothes on, go back out.

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Now you're warm.

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Your prediction of warm
clothes keeps your body warm

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is now upheld.

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So even with the most basic
idea of what clothes to wear,

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you have at one point in
your life, run the experiment

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a couple times in a row to
figure out what to wear.

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So if that prediction is false,

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the hypothesis must be modified,

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so change it until you
get one that is upheld.

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When that prediction is true

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only one small part has been tested.

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Going back to that drug
trial again I set up.

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Even if you did test it with everyone

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at the same exact temperature
fever, with the same amount

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of time being ill, with the same illness,

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because even different illnesses
could cause problems here.

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You might say okay, hey this drug worked

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on this particular illness.

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Is that further testing?

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Sure.

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Are there illnesses,
other temperature fevers,

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higher and lower, different age groups?

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So even if it's true, you still have to

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keep testing other variables.

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A hypothesis cannot be proven true.

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It can only be supported
'cause no matter what,

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you can never say a drug
will reduce fever 100%.

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It can be proven to be true
because all of a sudden

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sure, yeah I saw that, no
problem, the fever went down.

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In this particular instance.

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So you support your hypothesis
of what you thought.

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Now go back, change it up a
little bit and test it again

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with a slightly different variable.

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So you kind of think of it
as this big round robin here.

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You start with number one
observe and generalize.

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No problem.

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Then you form a hypothesis,
make a prediction,

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experiment and observe it
and then get to the modify

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and repeat as necessary.

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Odds are the very first time is probably

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not gonna be supported,

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so you modify the prediction,

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you modify the experiment, test again.

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Well this one might have been upheld,

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but good chance it probably
wasn't, so you go in again.

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Go through and test the prediction,

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test and experiment again
and keep going over and over

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until your hypothesis is upheld.

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Each time you retest it's a better chance

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the hypothesis will be supported.

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One of the biggest things,
one of the key things

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whenever you're sampling
with living organisms,

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you want a larger number of individuals.

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A larger number of organisms.

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'Cause if you test just two people well,

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there's a good chance two
of them will be positive,

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but the more individuals
you have the better chance

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of having a better representation
of the entire population.

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What you do is you take
that grouping of subjects,

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and you split it into at least two groups.

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These two groups should be random.

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Do not pick based on age,
or gender, or anything.

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It should be basic assigning
a number to each person

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then randomly picking those numbers out

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and put 'em in two groups.

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And you treat each of
these groups identically.

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I mean perfectly equally.

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The only difference is
there's one variable.

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The experimental group gets the treatment.

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The control group, the one
you're testing against,

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gets a placebo.

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It's important now because
it shows you, it takes

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the mental idea out of the picture.

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Because you can see what the mental idea

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of getting a treatment is,
but not really getting it.

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Placebo is nothing's happening.

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You're giving a false treatment.

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In this case they're
testing blood pressure.

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Did the treatment group, the
experimental group, end up

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with a lower blood pressure
than the control group?

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If the answer is yes, then
you support a hypothesis.

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But if it's no that means that probably,

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just the sheer mental idea
of getting a treatment

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was just as effective
as the actual treatment.

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Which means that treatment isn't really

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that effective at this point.

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It needs a little more modification.