The Scientific Method

1. What leads scientists to forming a scientific question and hypothesis?

2. Is the scientific method a linear process with a clear start and end point?

3. What makes for a good scientific question?

4. What is a hypothesis? What are the hallmarks of a good hypothesis, and why do scientists insist on using hypotheses with these properties?

5. Why is it important for scientists to form a hypothesis before they begin their experiment?

Collecting Data

1. Which of the following would be an example of quantitative data?

A) The flowers were yellow and orange
B) The shark's teeth were sharp
C) The redwood tree was 110 meters tall
D) The porcupine fiercely defended her porcupettes

2. A scientist records observations about the appearance of a spider's web woven after the spider is given caffeine. What kind of data is this scientist collecting?

3. You shoot your socks into the laundry hamper one night. Is this an example of accuracy or reliability?

4. Your teacher calls you the wrong name every.single.day. Is this an example of accuracy or reliability?

5. When Katniss Everdeen has a bow and arrow in her hands, she always hits her target. Is she accurate, precise, both, or neither?

Graphing Data

1. If we want to show what percentage of your class has brown eyes, green eyes, and blue eyes, what type of graph would we use?

2. If we want to show how the height of a swinging pendulum changes over time, what type of graph would we use?

3. We are testing how quickly a plant grows over time. Should time or plant growth be plotted on the x-axis?

4. What type of variable is plotted on the y-axis?

5. What is the purpose of a legend?

Analyzing Data

1. What does this graph show?


(Source)

A) Something is decreasing over a period of four years
B) Something is increasing over a period of four years
C) There has been no change over a period of four years
D) There is a negative correlation

2. What does this graph tell us about the number of U.S. households with less than $10,000 of yearly income?


(Source)

3. Let's say you collect the following data on number of kittens birthed by a mother cat: 3, 5, 4, 4, 3, 4, 2, 9, 2. What are the mean, median, mode, and range for these data? What do they tell us about the data?

4. A scientist does a study that shows test scores drop in the month of May. Since Mother's Day is in May, he proposes that Mother's Day is causing students to perform poorly on their tests. Do his findings demonstrate causation or correlation?

5. A scientist gives fifty plants the same amount of the same fertilizer and they all grow five inches taller than the fifty plants that weren't given any fertilizer. Would it be safe to say the fertilizer caused the plants to grow more?

Error

1. We use a scale that has not been calibrated and is 2.5 grams off. What type of error is this?

2. The air conditioning turns on as we are pouring a powder into our beaker and we notice that some of the powder is blown onto the desk. What type of error is this?

3. We decide to hold our graduated cylinder close to our face to read the measurement instead of keeping it on a flat surface. What kind of error is this?

4. Your expected value was 75 grams, but your actual value was 72 grams. What is the percent error?

5. What should we do if we know our data have an error?

Ethical Issues

1. What are ethics? Why are ethics important for scientists to understand?

2. Which of the following is not an ethical consideration for a scientist conducting an experiment?

A) Honesty
B) Collecting accurate data
C) Informed consent
D) All of these are ethical considerations

3. What ethical considerations must a scientist take when they are testing on humans?

4. True or false: All ethical issues in science are easily interpreted as right or wrong.

5. Why is the peer review process important to maintaining ethics in research?

Scientific Models

1. Which of the following is not an example of a scientific model?

A) A mathematical equation describing gravity
B) A hummingbird's wing flap pattern
C) A 3D representation of a flower's reproductive organs
D) A computer program that shows how the Earth orbits the sun

2. Why are models so useful to scientists?

3. True or false: Models are constantly being changed and updated.

4. If a scientist wants to show the structure of an atom, what type of model would be the best to use?

5. If a scientist wants to predict how the human population will change over time, what type of model would be best to use?

Communicating Results

1. Who peer reviews scientific studies?

2. Put the following in order from first to last step of communicating results.

A) The study is reviewed by peers
B) The study is published in a scientific journal
C) The experiment is performed, analyzed, and written up by the scientist
D) Results of the study are used to influence scientific thought, including theories
E) The results of the experiment are submitted to a scientific journal for review
F) The study is confirmed to be scientifically sound by a group of peers

3. What happens if a study is peer reviewed and found to have errors?

4. What are the benefits of peer review?

5. Why do scientists try to replicate published experiments?

Law vs. Hypothesis vs. Theory

1. What do we call a testable explanation for a phenomenon on a narrower scale?

2. True or false: If a theory gets enough evidence to support it, it eventually becomes a law.

3. The equation PV = nRT describes how gases will behave in different situations. Is this an example of a law, theory, or hypothesis?

4. Let's say a scientist wants to explain how the planets in a distant solar system orbit one another. Would this be an example of a law, theory, or hypothesis?

5. What happens when we get new evidence that does support a current law anymore?

Science and Technology

1. What does an engineer do?

2. Why is the field of engineering important to scientists?

3. Why is the field of science important to engineers?

4. True or false: Science and engineering are two fields that share the same purpose.

5. Do engineers use the scientific method?

Solutions

The Scientific Method

1. What leads scientists to forming a scientific question and hypothesis?

An observation of a phenomenon is what leads scientists down the scientific-question-and-hypothesis road. For example, if we observe a cronut for the first time, we might ask, "Does that cronut really taste like a croissant and a donut?" Let us know if you need help with the experiment.

2. Is the scientific method a linear process with a clear start and end point?

Not really. It's nice to sum it up that way for the sake of discussion, but in the real science world, science rarely goes in a straight line. Usually when we observe a phenomenon, we've got tons of questions. We then narrow them down and focus on one, but we might also have five different hypotheses we think could explain that phenomenon. After doing a little research, we might find that two of those hypotheses belong in the garbage. So we're left with three hypotheses, which we test, but we don't get results consistent with any of them. Now we need to do some more research and, of course, we have more questions, and if we start asking questions, we're gonna have to do an experiment to answer them.

3. What makes for a good scientific question?

A good scientific question is one about the natural world (sorry, zombies). It should also be able to be answered using natural processes and phenomena (sorry, Dumbledore).

4. What is a hypothesis? What are the hallmarks of a good hypothesis, and why do scientists insist on using hypotheses with these properties?

A hypothesis is a testable prediction about something we've observed. A good hypothesis is one we can test using an experiment or by collecting observations. It is also falsifiable, which means it is possible to prove the hypothesis false. Setting up a hypothesis to be testable and falsifiable helps scientists to eliminate the stinkers and focus on confirming (and reconfirming) the results of the ones that panned out, which keeps our knowledge moving in the right direction—forward.

5. Why is it important for scientists to form a hypothesis before they begin their experiment?

The purpose of an experiment is to gather evidence that supports or refutes a hypothesis. Without a hypothesis to test, we're not doing science so much as making a mess. The hypothesis helps us set up our experimental procedures, determine what variables we need to test, decide what kind of evidence needs to be collected and the best way to do that, and gives us a benchmark to refer back to when we finish our experiment. The hypothesis is like the compass for our experiment, keeping us on track and pointed in the right direction. Without it, we'd definitely end up lost in the woods.

Collecting Data

1. Which of the following would be an example of quantitative data?

A) The flowers were yellow and orange
B) The shark's teeth were sharp
C) The redwood tree was 110 meters tall
D) The porcupine fiercely defended her porcupettes

The correct answer would be (C). Quantitative data involve numbers, and this is the only option that fits the bill. Also, porcupettes is the correct term for a baby porcupine. Just in case you were wondering.

2. A scientist records observations about the appearance of a spider's web woven after the spider is given caffeine. What kind of data is this scientist collecting?

This would be an example of qualitative data. The scientist is recording observations about the qualities of the web, not taking measurements or recording quantities.

3. You shoot your socks into the laundry hamper one night. Is this an example of accuracy or reliability?

Your footsie free throw is an example of accuracy. Those socks made it exactly where they needed to go, so go ahead and high five yourself (just don't let anyone see).

4. Your teacher calls you the wrong name every.single.day. Is this an example of accuracy or reliability?

Your teacher may not be good at names, but at least they have reliability on their side. And maybe you do kind of look like a Pat…

5. When Katniss Everdeen has a bow and arrow in her hands, she always hits her target. Is she accurate, precise, both, or neither?

Katniss is both precise and accurate. Totally what we want on our side when we're trying to take down the Capitol. Or doing a science experiment.

Graphing Data

1. If we want to show what percentage of your class has brown eyes, green eyes, and blue eyes, what type of graph would we use?

A pie chart works great for showing parts of a whole, like different eye colors in a classroom, and is especially awesome for dealing with percentages. A bar chart would do it, too, in a pinch; just be careful setting up the y-axis so people realize we're handling percentages here.

2. If we want to show how the height of a swinging pendulum changes over time, what type of graph would we use?

Line graphs are just the ticket for showing change over time. Just don't let that pendulum hypnotize you into choosing a bar graph.

3. We are testing how quickly a plant grows over time. Should time or plant growth be plotted on the x-axis?

Time should be plotted on the x-axis since it's the independent variable.

4. What type of variable is plotted on the y-axis?

Dependent variables, or the variables being tested in the experiment, are typically plotted on the y-axis.

5. What is the purpose of a legend?

A legend is your graph in a nutshell. It summarizes your data and experiment, along with the units you used and any cool, or uncool, results that popped up.

Analyzing Data

1. What does this graph show?



A) Something is decreasing over a period of four years
B) Something is increasing over a period of four years
C) There has been no change over a period of four years
D) There is a negative correlation

This graph shows that something is increasing over a period of four years, so answer choice (B) is the way to go.

2. What does this graph tell us about the number of U.S. households with less than $10,000 of yearly income?



This graph shows that the number of households with an annual income of less than $10,000 is decreasing. We know this because the red line shows a downward trend.

3. Let's say you collect the following data on number of kittens birthed by a mother cat: 3, 5, 4, 4, 3, 4, 2, 9, 2. What are the mean, median, mode, and range for these data? What do they tell us about the data?

If we add the numbers up and divide by how many we have, we end up with a mean of 6 kittens. Our range of data is 7 kittens, if we subtract the smallest number from the largest. The mode, or number that occurs the most is 4 kittens, and our median, or number in the middle is 4. Based on these data, the mode tells us that it is most common for a cat to have 4 kittens. When we compare our median of 4 to our mean of 6, we can see that our data is skewed a bit to the right.

4. A scientist does a study that shows test scores drop in the month of May. Since Mother's Day is in May, he proposes that Mother's Day is causing students to perform poorly on their tests. Do his findings demonstrate causation or correlation?

This would be an example of correlation. It's purely coincidence that Mother's Day falls in the same month that students perform more poorly on tests. Do we know the actual cause? It could be any number of things—end of the year burnout, prom, sports, it's sunny outside and no one wants to study…Just remember that we can't claim causation without evidence to support it.

5. A scientist gives fifty plants the same amount of the same fertilizer and they all grow five inches taller than the fifty plants that weren't given any fertilizer. Would it be safe to say the fertilizer caused the plants to grow more?

Yes, we've got a pretty good sample size here and very precise results. With that kind of evidence, we can say that the fertilizer is causing the plants to grow more and it isn't simply a coincidence.

Error

1. We use a scale that has not been calibrated and is 2.5 grams off. What type of error is this?

This would be an example of equipment or systematic error. It's tough to realize when these errors happen, because all of our data will reflect the same error and nothing will stand out. That's why it's always a good idea to make sure that equipment is calibrated before we get started.

2. The air conditioning turns on as we are pouring a powder into our beaker and we notice that some of the powder is blown onto the desk. What type of error is this?

This is a classic example of random error. That puff of air from the air conditioning happened to occur at just the right time to introduce some error into our experiment. It's just a random, unfortunate turn of events. Since we witnessed some of the powder being blown onto the desk, we can go ahead and discard this data point and repeat the experiment a few times (with the AC turned off). We'll just be sure to discuss the interrupting air conditioner and discarded data in our conclusions.

3. We decide to hold our graduated cylinder close to our face to read the measurement instead of keeping it on a flat surface. What kind of error is this?

This, friend, is called human error. Not using equipment properly, like holding a graduated cylinder to read it instead of reading it while it's on a flat surface, is a major source of error, and one that can easily be prevented. Know your equipment, people.

4. Your expected value was 75 grams, but your actual value was 72 grams. What is the percent error?

To get our answer, we use this equation: . So, if you subtract 72 grams from 75 grams, you get a difference of 3 grams. Divide 3 grams by 75 grams, multiply by 100 and you end up with 4% error.

5. What should we do if we know our data have an error?

If we suspect our data have an error, we should do our best to get rid of whatever is causing the error (even if it means suggesting our lab partner go check on something in the closet) and repeat your experiment. Then be sure to discuss the source of the error and the data it produced in our conclusions.

Ethical Issues

1. What are ethics? Why are ethics important for scientists to understand?

Ethics are basically a set of rules that make it clear what behaviors are right or wrong. It is important that scientists understand ethics, because scientists are in a position to influence the decisions people make about their health, safety, and well being. People trust that scientists have conducted their research to the best of their ability, have analyzed and reported their findings honestly, and are looking out for the best interest of everyone involved. If a scientist betrays that trust, they can not only cause undue harm, but any further studies they attempt to do will be given the side eye and a one-way ticket to the shredder.

2. Which of the following is not an ethical consideration for a scientist conducting an experiment?

A) Honesty
B) Collecting accurate data
C) Informed consent
D) All of these are ethical considerations

Can't go wrong with (D). A scientist must be honest in reporting the results of their experiment, as well as ensure they collect their data accurately. They must also inform any human participants of what they can expect from participating in the study.

3. What ethical considerations must a scientist take when they are testing on humans?

When scientists use human test subjects, they must get informed consent. This means they've made sure their participants know exactly what is going to happen during the study and any effects the study may have on them before they dive in. Scientists also need to protect the privacy and dignity of their test subjects and ensure that any risks are outweighed by the benefits of the study.

4. True or false: All ethical issues in science are easily interpreted as right or wrong.

This would be false. Issues like honesty are pretty easy to get right, but some issues are more complicated and have more than one viewpoint to consider. For example, is it ethical to perform harmful tests on animals if it will save human lives? Ultimately, scientists have to ensure the benefits outweigh the risks.

5. Why is the peer review process important to maintaining ethics in research?

Peer review is another way to check a scientist's work to ensure they are conducting their experiment and reporting their findings ethically. It provides another set of eyes in case something like falsified data or unacceptable procedures slipped by an IRB or IACUC.

Scientific Models

1. Which of the following is not an example of a scientific model?

A) A mathematical equation describing gravity
B) A hummingbird's wing flap pattern
C) A 3D representation of a flower's reproductive organs
D) A computer program that shows how the Earth orbits the sun

In this case, we wouldn't consider a hummingbird's wing flap pattern (which happens to be a figure eight, in case you were wondering) a scientific model, because it's the real deal. Can we make a model to understand the wing flap pattern of a hummingbird? Sure can.

2. Why are models so useful to scientists?

Scientists are big fans of models because they help them to understand stuff that they can't observe directly. You know, the stuff that happens too fast or slow or is too small or big to wrap our eyeballs around.

3. True or false: Models are constantly being changed and updated.

This one is all true. As we learn more about the natural world, sometimes our models have to change to keep up. Just like when everyone thought the Earth was flat, but a few scientists made some observations that helped shift the flat Earth model to a round Earth model, and, well, the rest is history.

4. If a scientist wants to show the structure of an atom, what type of model would be the best to use?

Some sort of 3D model would be the way to go here. That's usually the case when we want to show the shape or structure of something, since graphs and equations aren't really good at that sort of thing.

5. If a scientist wants to predict how the human population will change over time, what type of model would be best to use?

Graphs are great for modeling change over time. We can take what's already happened and use it to predict what will happen in the future by extending the line on our graph in the same direction. Looks like we're going to need some more room here on Earth.

Communicating Results

1. Who peer reviews scientific studies?

Scientists who work in the same field as the study are the ones who will peer review the study, since they're knowledgeable on the subject matter. Let's say we did an experiment to determine how a new wing shape affects the aerodynamics of an airplane. Scientists who study aerodynamics and engineers who build airplanes would be the ones reviewing our study. The botanists and paleontologists are off the hook for this one.

2. Put the following in order from first to last step of communicating results.

A) The study is reviewed by peers
B) The study is published in a scientific journal
C) The experiment is performed, analyzed, and written up by the scientist
D) Results of the study are used to influence scientific thought, including theories
E) The results of the experiment are submitted to a scientific journal for review
F) The study is confirmed to be scientifically sound by a group of peers

The correct order of operations here is (C), (E), (A), (F), (B), (D).

3. What happens if a study is peer reviewed and found to have errors?

Well, the scientist that submitted it may spend a day or two weeping in the corner, but then they'll take the feedback they got from their peers and fix it up so they can try to publish it again.

4. What are the benefits of peer review?

Having a study that has been peer reviewed is beneficial because it is more trustworthy. Scientists who are rock stars in the field have read it and given it the thumbs up, which means it probably well-designed, logical, and advancing our understanding of the natural world. In short, it rocks everyone's socks off.

5. Why do scientists try to replicate published experiments?

No need to tattle, this isn't the case of a copycat. Replicating an experiment is an important aspect of the peer review process. If scientists are able to repeat an experiment and get the same results, that just adds more evidence to support the original hypothesis. And we know how much scientists love evidence. If scientists repeat the experiment, but can't repeat the results, they'll know they need to look a little more closely at the original experiment's design and execution for a sneaky error (or a sneaky scientist).

Law vs. Hypothesis vs. Theory

1. What do we call a testable explanation for a phenomenon on a narrower scale?

This would be a hypothesis. Remember that hypotheses have to be testable, and they're a potential explanation for something we've observed on a relatively narrow scale (think changes to a bug population vs. all of evolution).

2. True or false: If a theory gets enough evidence to support it, it eventually becomes a law.

This one is false, friends. A theory is a way to explain a complex phenomenon, while a law is more of a description of something we've observed. A law tells us what is going on; the theory is there to tell us why.

3. The equation PV = nRT describes how gases will behave in different situations. Is this an example of a law, theory, or hypothesis?

We've got a law on our hands here. How do we know? Well, the equation should be our first clue. It's also describing something that's pretty specific, rather than trying to explain why this equation holds up.

4. Let's say a scientist wants to explain how the planets in a distant solar system orbit one another. Would this be an example of a law, theory, or hypothesis?

This would be an example of a theory. Our friend the scientist is trying to explain something pretty complex that can't be turned into an equation. That rules out laws. Plus, whatever their explanation ends up being, it's going to have all kinds of previously unseen implications; while some hypotheses can lead us in unexpected directions, any theory worth its salt is going to shake up our understanding of the world. May the force (of gravity in this case) be with them.

5. What happens when we get new evidence that does support a current law anymore?

We change the law! It's not that easy, and we need a lot of evidence, but laws, theories, and hypotheses are always subject to change as we learn more about what's goin' on in the natural world.

Science and Technology

1. What does an engineer do?

An engineer uses their knowledge of science and math to solve problems. Usually there's a new device or product involved. Engineers call these toys.

2. Why is the field of engineering important to scientists?

Engineers make new tools for scientists so they can expand their knowledge of the natural world.

3. Why is the field of science important to engineers?

Scientists are constantly making new discoveries about materials, chemicals, or other parts of the natural world that engineers can hijack and use in their own creations.

4. True or false: Science and engineering are two fields that share the same purpose.

This is mega false. Science and engineering definitely rely on each other's discoveries, but the purpose of science is to expand our knowledge, while the purpose of engineering is to build stuff to solve problems.

5. Do engineers use the scientific method?

Sure they do. Research and development is all about identifying a problem, coming up with a proposed solution, testing it, making revisions, and starting the process over again. Sounds pretty scientific method-y to us. It's just that scientists tend to ask questions about the nature of the universe, while engineers are asking, "How many rubber bands would it take to launch a basketball into the air?"