Anytime we want to solve a problem or answer a question in science, we need to use what's called the
scientific method. This is sometimes called
scientific methods because the plan is not always exactly the same. You can do these steps in different orders. A
scientific method in general is a plan to gather,
organize, and communicate information. We call that information data usually.
To get our problem or a question that we want to do an experiment on, we end up making an observation
and an inference. An observation is when you get information from your senses,
so it's something you see or something you hear, etc.  An
inference is what you end up assuming about that observation. So, I can observe that
someone is wearing a blue shirt. My inference could be
that that person's favorite color is blue. Now, that may not be correct,
but it is
somewhat related to the observation so to find out if that is correct we have to do an experiment, so
our example of an experiment is going to deal with carrot seeds.
Let's say that I plant some carrot seeds and after about a week. I see that there has been no growth at all.
They're not sprouting. I
would then want to make an inference about that so that I can grow carrot seeds properly.
My inference might be that the soil around the seeds is too compact
and it's not letting the roots grow as they should, so
I take that inference
and I change it into a question. Do carrot seeds grow better in compact soil ( nice and tight around the seed) or
in loose soil, where it
is more loose around the seed?
To answer this question, I'm going to first propose an answer to it. That's my
hypothesis. It has to be testable, meaning I need to be able to test that with an experiment.
So, for my hypothesis, it starts with the word "if" and the word, "then" is in it as well. We call this an if-then statement.
So in the "if" part of it, that's what I think is going to happen
or what I think is going to be better in this case.
So, in this case, if I start with "if carrot seeds grow better in loose soil" that means I think loose soil would be better
for the seeds. You could say, "if the carrot seeds grow better in
compact soil...." blah blah blah if you think compact soil will be better.
The "then" part tells you how you will know if you are correct or not,
so if those carrot seeds are going to grow better in loose soil,
I will know this because the seeds grown in loose soil will grow faster than the seeds growing in compact soil.
That's my hypothesis for this experiment. I
need to set up my controlled experiment to test my hypothesis. A
controlled experiment only has one variable that has changed on purpose. A variable is anything that could change in the
experiment. So, with plants, there are lots of variables. So, we know that plants need water.
So, it could be the type of water, the amount of water,
the temperature of the water, any of those things are considered variables. We only want one of those things to be different between
my plant that has compact soil and my plant that has
loose soil. In this case, the thing that's different is how compact the soil is. In
a controlled experiment, I have two
groups. The control group in this case would be my current idea. My current idea is to
make sure that the soil is nice and compact around the seed.
This could also be a blank, so if I'm testing like, different kinds of water, my control group might just be, you know,
complete, you know, regular water. Where my
experimental groups, the new ideas, could be like, salt water, sugar water, or something like that.
So, control can be a blank or it can be what you currently use or your current idea.
Experimental group is your new idea. So in this case, my new idea is
using loose soil, instead of compact soil, and I could test other things, too. That's why I have
an s in parenthesis here. I could have lots of experimental groups, so I could use,
like I said before, sugar water or salt water. Those would both be experimental groups compared to just regular water.
So, when I set up my experiment, I typically have these four parts.
The first one is the independent variable.
That's what I'm
changing on purpose. In the case of this experiment, the thing that I'm changing between these two carrot seed plants is
how compact the soil is. That's it.
Everything else needs to stay the same. If it's not the same at the end when I have two different results,
I don't know if it's because I
used a different type of water with this one, or it had more sunlight,
etc. The only way I know for sure it was the compactness of the soil is if that's the only thing that has changed.
The dependent variable is what we think is going to be affected by the
independent variable. So, in this case,
I think that changing the compactness of soil is going to affect the speed of growth of the seeds.
My constants - those are all of those things that I need to keep the same, so how much water each of my plants get
needs to be the same, the type of water needs to be the same. So, notice that these both deal with water.
When I ask you for constants, just writing water is not enough information.
You need to tell me what it is.... what it is about the water
that's gonna stay the same. The amount, the type, the temperature.
Also, notice that soil
would not work up here for the independent variable because yes, I'm changing something about the soil,
but I was really specific and I said that it has to be how compact the soil is.
We would still use the same type of soil , all we're changing is how compact this soil is. So, anything
I keep the same, those are my constants. My control we talked about on a previous slide.
It's either a blank or it's your current idea. My current idea is to use compact soil.
So, I'm going to compare the growth of the seed in compact soil compared to loose soil and loose soil is my experimental group.
Once I do the experiment and I get my results and I create these fantastic tables and charts and graphs to
demonstrate what my results have been. I come up with my conclusion.
This is the answer to my question, and it's either going to support my hypothesis
or it's gonna reject it. So let's say I do my experiment and I find out that
oh, the seeds is in the loose soil grow
faster than in the compact soil. So, the seeds planted in loose soil grew faster than the seeds in the compact soil.
This means that my hypothesis is supported
because I was right. My hypothesis is correct,
so we say it's been supported. If it was wrong, I would reject the hypothesis. No matter what happened here,
no matter whether you are right or wrong, you end up testing that hypothesis again and again.
So, I don't just stop there and say, "okay great, I
predicted the future and everything's fantastic." I have to do that over and over and over again to see if
those results are always the same.
When I do that, I can end up, and scientists end up, making what we call scientific theories. Now,
this is not the kind of theory that we talk about
every day in our everyday language. A
scientific theory is an accepted hypothesis, so it means that it has been
accepted by the
scientific community.
It means that there have been lots of experiments to show that it is correct, at this point.
This explains a phenomenon, so my example is the theory of plate tectonics. The theory of plate tectonics explains
why we have mountains and earthquakes and volcanoes,
etc.
and it is an accepted hypothesis. A
scientific law is a summary. Notice that a theory explains and a law is going to summarize.
So, in this case, I don't know why this happens, but
that's not the point for the law. The law is just, "this is what happens",
doesn't explain why. So, my example of a scientific law is one of Newton's laws. An
object at rest stays at rest, unless acted upon by an outside force. That's an example of a law. Doesn't tell us
why it happens. It's just summarizing what we see in our everyday life.
Both of these things,
theories and laws, are accepted by the scientific community. It's the best that we have so far
to summarize our observations and to explain what we see in our everyday lives.
Both of them could change depending on getting new technology, new perspectives,
different people thinking about it in a different way,
etc., etc. So, keep in mind, science is
supported by observations,
supported by
experiments, but those ideas could change over time.
Last thing is scientific models. In science, we use a model, which is going to represent an object or an event.
So, to model an atom, 'cause I can't see an atom, I can
come up with some sort of visual to help me understand
what is really going on in an atom and I can use computer programs to model weather processes
or if I want to determine what it would be, like if an earthquake
happened in this particular place, there are computer programs that can model what that would be like without actually having to experience it.
So, those are scientific models.
There is a scientific method simulation. It's on a website and it deals with an experiment with crickets.
If you complete this, you will receive some extra credit points.
This is the link right here, and I will describe to you in class more about
things, such as when it is due.
