The Scientific Method

Science is a Way of Knowing

Science is a way of knowing the natural world. In factA statement based on direct observation that is repeatedly confirmed., the word “science” derives from a Latin root meaning “to know.” There are two main scientific approaches: discovery science and hypothesis-driven science. Scientists often use a combination of these approaches to explore nature.  Science doesn’t say: here are the facts.  Science seeks to say: this is what we know right now.  This is why science is ever changing.  As we, as humans, increase out technology, we can explore more areas of the globe.  When I say areas, I mean things like volcano craters and deepAway from the surface of the body. ocean trenches, but also the bacterial colonies on the headRounded proximal end that fits into the acetabulum of the hip bone. of a pin and the unseen world that covers everything we touch.  Can you imagine what science was telling people before the microscope? 

Discovery Science

Discovery science is the process of describing nature without any preconceived expectations. For example, Jane Goodall studied the social life of chimpanzees mainly by spending thousands of hours in the field watching them. You do this in your own life when, for example, you walk into a restaurant and note each of the different menu items available for selection. Like Jane Goodall, you are actually performing discovery science; you are observing the world around you and discovering what it contains. In discovery science, general principles are sometimes inferred from a set of specific observations. For example, Jane Goodall observed that some chimps strip twigs and then poke them into termite holes. From this, she concluded that humans are not the only animals to make tools. In your real-life example, after you note all of the food choices available in the dining hall, you may conclude that vegetarian options are rare in your cafeteria. Many important scientific advances, such as the description and classification of organisms, and the mapping of the human genomeThe complete set of genetic material in an organism., have resulted from the discovery approach to scientific inquiry.

Hypothesis Driven Science

In contrast, hypothesis-driven science involves constructing a specific, testable explanation for a phenomenon based on a set of observations. After testing this explanation, conclusions can be drawn depending on whether the results you obtained support or refute the explanation. Hypothesis-driven science typically follows a series of steps called the scientific methodA systematic approach to investigation using hypothesis testing.. The scientific method is a loose set of guidelines for discovery, intended to lead a scientist from an observation to an explanation.  This is the method that we will employ in the labs.  Before beginning a lab, you have reading or research to do that allows you to collect observations and form a hypothesis.  Then, you will test that hypothesis in the lab activity.  It’s important to do this and have a clear direction in testing a hypothesis.  This is like ordering the school children into lines before going out onto the playground instead of just letting everyone just run out there screaming at the top of their lungs.  It’s the process, not the outcome, that designates your labs as science.

Observation & Hypothesis

Ever see these things? Peeps?  Just a sugary marshmallow.  My mother loved these things.    Observation is noting a fact or occurrence in the natural world. You notice that, here in northeast America peeps tend to get very abundant every year around April, then they taper off and reappear again in October.  This first observation doesn’t really lead you to a hypothesis.  It takes more than that.  More observations, called research are needed.  You incorporate some research from the natural world: some animals reproduce on an annual basis and animal populations will show this increase in number if counted.  Observations typically lead to a hypothesis, in this case, “Peeps have an annual breeding cycle that corresponds to temperature.”  Note how the hypothesis is a statement, not a question.  Also, the hypothesis has an expectation.  It doesn’t say: The experiment will explore the breeding cycle and temperature.  The hypothesis makes a prediction.  Remember we are not running screaming out onto the playground, we have direction.

A hypothesis is a testable explanation for an observation.  It’s important to note that a hypothesis is not a shot in the dark, but based on prior knowledge. Hypotheses are stated clearly as a statement: Peeps breed more with an increased temperature.  This leads to a prediction: namely, if I go to a local peep breeding ground, I will see an increase in the peep population as it gets warmer in the Spring. It’s important to remember that a hypothesis has to be testable.  This can be tough when we are considering the natural world.  Yes.  This is why hypothesis-driven science usually takes place in the lab.  These investigations have to be controlled or managed carefully to proceed correctly.  This is hypothesis-driven science..

I want to bring up something really important here.  Hypotheses don’t have to be correct.  In fact, in this class you will often have a wrong hypothesis.  It’s OK.  What is important is your ability to know if your results support your hypothesis or not.  If that data doesn’t support why you thought, that is perfectly OK.  Your hypothesis isn’t a shot in the dark, it is based on research but your experiment is only one test.   

Variables

I like to start with the dependent variable, although everyone tends to start with the independent.  The dependent is pretty straightforward because it is usually the data that you collect.  When we write about experiments, students often forget to describe this one.  Let’s look at some of these hypotheses to understand.  How might you go about testing the statement that corn plants grow taller with fertilizer.  You might grow corn in different concentrations of fertilizer like 20% and 40% and so on.  That makes sense.  And then, you might record heights after letting them grow for a certain amount of time.  What’s the data you collect?  What do you measure?  Yes!  The heights of the plants is the dependent variable.  This data will allow you to say: Yes, corn plants grow taller with fertilizer.  Or not, as the case may be.  Let’s skip to the third hypothesis here.  What is the data you are collecting? Price!  Yes!  This is what will indicate which jacket is cheaper.  Before we do the remaining hypothesis, let’s recognize something.  Neither of these two hypotheses here tell you that height or price is the dependent variable.  You had to think a little bit about how you would test these.  Keep this in mind for the last one.  What might be the data we could collect for this one?  You might be saying: well, I would measure the enzyme activity.  Yeah, I’ll take that.  It’s vague, but without really thinking about an experiment, we can’t get more specific.  For example, lactase digests lactoseA disaccharide sugar found in milk. produce glucoseA simple sugar that is the main source of energy for cells..  You could measure the glucose.  But that’s so specific!  This is why defining variables can be difficult.  They are vague sometimes. 

Variables

This is what I mean by a controlled or managed experiment.  In a hypothesis-driven investigation, we define variables very specifically.  The first is usually the most confusing to students.  The independent variable is what is being tested.  The independent variable is determined by the investigator.  Let’s look at some hypotheses and try to determine the independent variable which must be the only thing being tested.

OK, so corn plants grow taller with fertilizer.  I’m not debating this with you, it’s just an example.  What are we testing?  You might say corn plants.  OK, but wrong.  Let’s think of what we might do to test this statement.  We might grow corn in two fields and use fertilizer in one of them and not the other.  You are varying and manipulating the fertilizer.  Right?  That is what we are testing, the effect of fertilizer. 

Let’s think about the next statement because practice is the way to understand the independent variable.  We could use lactase, which is the enzyme that digests lactose to test this.  You might put lactase with some lactose in different temperatures and measure something to indicate the activity.  What are you intentionally manipulating to be different?  The temperature!  Yes! 

Let’s do the last one.  How would you go about testing if Store X has the cheapest price?  You might go to Store Y Store Z and Store A and write down the price each store offers.  You are choosing to go to these different stores.  The stores are the independent variable.  Let’s recognize something here for independent variables.  You might want to define it as: the thing that is being tested.  This statement usually leads you to the dependent variable, the height of the plant, the price of the jackets.  This is why you have to ask: what would I be intentionally manipulating to set up this experiment?

Confusion

Controlled variables are usually easy for students to recognize.  There are usually many of them and they are all constant, like using the same corn plants, the same enzyme, and the same jacket.  The problem with controlled variables is that they get confused with what is called the control.  So, the control is different than the controlled variables.  Please know that right at the outset here.  The control is a basis of comparison.  This is really hard to define for some experiments.  Let’s start with easy ones.  We might amend this first experiment with corn plants so that we are growing plants with different concentrations of fertilizer.  We would need some plants grown with no fertilizer as a basis of comparison.  Plants not grown with fertilizer are the control.  Hmmmm…this one is tough.  What do we designate as the control for temperature?  0?  Room temp?  You get to decide, but you better be pretty clear about it.  How about this…when you set up this experiment, you combine the enzyme with some other goo and it all starts out at the same temperature.  This is the basis of comparison.  I know a bit tougher.  How about this one.  Are you thinking about a placeboA substance with no therapeutic effect used in control groups. group, or a group that you don’t give Drug X?  Yes.  So, a bit more confusing.  When you encounter these concepts in later labs, I urge you to come back to this presentation and refer to it.  Comparing your experiment to these examples can help you.  As we went through these variables, the definitions don’t help, right?  The examples help.

Analysis of Data

Those last three slides are sometimes better understood with a graph.  If you are having trouble thinking about the experiment itself, you might be able to look at a hypothesis and think about what kind of graph you might make.  That’s good because the dependent variable is usually on the y or vertical axisSecond cervical vertebra; has the odontoid process (dens) for pivoting head (“no” motion)..  Easy enough, think about the corn plant height and jacket price.  The independent variable is also usually along the x or horizontal axis.  Let’s go back and think about the peeps.  We wanted to see if they reproduce more in the Spring.  So, we chose to measure at different times during the year.  We determined that, so that’s our independent variable and yes, it is on the x axis here.  We counted the peeps each time we did our measurement, which is on the y axis too.   It’s important to let your data determine the right type of graph to use.  What display would best show your conclusion?   Our graph shows that peep population increases to a peak in April, then decreases until a small bump in October.  We can compare this to our expectation in the hypothesis. 

Line or Bar Graph?

Before we go on, I want to point something out.  Many students who take this course are business majors.  In business, you are often creating graphs as displays of data.  There are different rules in business.  If you are a business major, you might default to a bar graph and you might want to put the independent variable along the vertical axis.  I appreciate that you’ve been well trained to do that, but we apply a different display here.  Check out the graph on the left.  The x axis doesn’t make any sense!  Right?  You don’t have the ability to rearrange those numbers like that.  They have a predetermined sequence. Think of something like temperature, or age.  You can reorder them.  When this is true, a line graph is the way to go.  Could I use a bar graph?  I could, but it’s better to use a line graph. 

Let’s look at the bar graph on your right.  The meats along the x axis have no predetermined order.  I could have gone the alphabetical route with them.  Since they have no predetermined order, I decided the order of them.  And, I liked this order because it showed a nice increase.  Maybe you want a decrease; that’s fine.  We have choices here, unlike the line graph.  This is why we use a bar graph, because the independent variable, along the x axis, doesn’t have a predetermined sequence.  I want to ask you to be aware of when you have this choice.  And make a good choice.  Don’t just slap stuff up on a graph.  Take a step back, and ask, can I make this prettier?  Seriously.  Presentation counts here.

Conclusion

Getting back to our peeps.  Once we’ve generated the data and make a pretty display, we have to interpret it.  We can’t just say: here’s the data, you figure it out!  We have to narrate the data.  Think about your textbooks when they present graphs.  They are referred to in the text and usually explained.  We have to do the same thing.  Before we get started there is something that is oh so useful to do.  You have to remind yourself what you set out to do.  Sometimes we forget.  Our hypothesis was that peeps reproduce in the Spring.  Our data partially supports our hypothesis.  As temperature rises in the transition from winter to spring, peep populations increase.  However, they decrease in the summer as temperature continues to rise.  The small bump in October could be due to a brief temperature burst commonly known as an “Indian Summer.” 

As a student, rejecting your hypothesis is just as important as accepting it.  When accepting your hypothesis, it’s important to suggest a next experiment to keep the overall investigation going.  Is there an optimal temperature for peep reproductionThe process of producing offspring.?  Is that why we see two increases in population in the year?

When your results do not support your hypothesis, which is often the case in science, you can revise your hypothesis or construct a new one and then repeat the method. You may thus end up running through the scientific method several times in order to explain the observation that began your inquiry. 

Peepresearch.org

As you may have surmised, you actually use both discovery science and hypothesis-driven science every day, though you may not think of it as such. If you pay attention, you will find yourself following the scientific method many times in your daily life. Therefore, you already have a lot of experience with these types of inquiry and you’re well on your way to understanding the scientific process.

You should really check out peepresearch.org.  Although a ridiculous application of the scientific method, the mock experiments on the website carefully use the steps of the scientific method.  So, just a reminder that the scientific method is a way of knowing.  In our case…a way of knowing peeps.