Human Biology: The Scientific Method

t the volleyball picnic was a boy who was blowing bubbles. bubbles Tony, a Clermont grad and former biology student, wondered, “What’s the biggest bubble this boy can blow?” and decided to conduct an experiment to determine the answer to that question. Tony had learned in biology class that the Scientific Method is a logical sequence of steps that a scientist uses to answer a question, solve a problem, and/or to make new discoveries, and thus, Tony decided to use the steps in the Scientific Method to determine how large of a bubble the boy could blow.

The Scientific Method

Here are the steps Tony followed:
Observation	–	Tony saw the boy blowing bubbles, and noticed that the bubbles were all different sizes. That’s when Tony became curious about the maximum size the boy could produce.
Question	–	From that, the question arose in Tony’s mind, “What’s the biggest bubble this boy can blow?”
Hypothesis	–	Remembering to use the metric system, Tony said, “I think this boy should be able to blow bubbles that are about 1 m long, as long as the wind is not blowing.”
Prediction	–	Tony thought, “If it is true that the boy is able to blow bubbles 1 m in length when the wind isn’t blowing, and if I use a meterstick to measure the length of some bubbles when the wind is and is not blowing, then I should be able to see bubbles of that size when there is no wind, but I should not be able to see bubbles that large when the wind is blowing.
Experimental Design	–	Tony borrowed a meterstick from Farmer Melanie, with which to measure the bubbles. Tony’s control group was to include 10 bubbles blown when the wind was gusting, and the experimental group was to include 10 bubbles blown when the wind was still. Tony planned to calculate the mean and standard deviation for each group of bubbles.
Data Collection	–	Now, Tony was ready to collect some data. Each time the boy blew a bubble, Tony ran up to it to measure it. Tony could see that, when the wind was still, many of the bubbles, initially, looked about the same length as the meterstick, but alas, whenever Tony tried to place the meterstick directly next to a bubble to measure it, the bubble popped, and so Tony “never got any data.”
Conclusions	–	Tony was disappointed by the results and felt that the experiment was a “failure.” However, then Tony remembered something from biology class: if the data aren’t what you thought you’d get, that doesn’t mean the experiment is a failure, but merely that the data show something other than what you intended. Tony thought about the experiment and realized that what the data (non-measurements) suggested was that bubbles will pop when touched with the meterstick and cannot be measured that way. From that, Tony realized there was a problem with the experimental design that was being used. Tony decided to alter the experimental design and to, instead, use a digital camera to photograph each bubble as it was being blown, then by examining the photographs, compare the length of the bubbles to the height of the boy (which could easily be measured).
More Testing	–	Tony tried collecting data via the new method, and found that it was fairly easy to photograph the bubbles. The wind speed (still or gusting) was recorded each time a picture was taken. The height of the boy was also measured. The photographs were downloaded onto Tony’s computer, and the sizes of the bubbles were compared with the height of the boy. When the averages were calculated, Tony found that the average bubble length in still air was 97 cm and in wind gusts was 63 cm. From that, Tony was able to conclude that, indeed, the data supported the hypothesis that in still air, the boy was able to blow bubbles of about 1 m in length. Tony also remembered that an experimental conclusion is only good for the conditions under which the experiment was conducted, and realized that if it would be raining, if the concentration of the “bubble juice” would change (if someone decided to dilute it), or if the experiment were to be repeated in winter, any of those factors could change the outcome.

Background Information

Some links to other, related information on our Web server
Bio 104 Scientific Method	–	Background information and activities related to the scientific method of discovering new information

Your Assignment
Design and Perform an Experiment

Is there something around your house or yard that can be studied via the scientific method? For example, will “too much” candy really make your child “hyper”? Does fertilizer really help grass or do coffee grounds help houseplants to grow better? Are there any interesting things you’ve observed and about which you’re curious? For example, have you noticed that if you eat breakfast, you seem to have more energy throughout the day or that it seems like, every time you eat wheat, 2 hr later, you have a stuffy nose? To illustrate how the Scientific Method can be used as a tool to solve problems and answer questions, based on your own curiosity about the world around you, you are asked to go through all the steps involved in designing and doing a simple experiment. Don’t think that you have to come up with something grandiose and complicated! Remember KISS: Keep It Simple! For those of you with children, this might be a project in which they could be involved. The grading criteria for this assignment are given below, and you should also refer to those as you work on the assignment. A total of 52 points is possible.

Think about, and maybe discuss with your family and friends interesting things that you notice in your daily life and in the world around you which awaken your interest or arouse your curiosity. It might be something as simple as noticing that houseplants on the second floor of your home seem to need to be watered more often than houseplants grown in the basement or that as you are walking around your yard, the air feels cooler when you are under a tree than when you’re standing out in the open. What interesting observation can you make about some aspect of what you’ve been discussing and upon which your experiment will be based?
Based on your observations of the world around you, pose a question about the thing which you have observed: for example, “I wonder if more of the houseplants’ water evaporates on the second floor (maybe due to airflow?) than in the basement?” or “Is the air under the tree really cooler?” Keep in mind that whatever you come up with should be simple and do-able, not grand, time-consuming, and impossible. We’re not out to conquor the world, here, but rather, to illustrate how to use this method of problem-solving.
Develop a hypothesis (one possible, tentative answer to your question) about some specific aspect of your question that could be tested using the scientific method: for example, “I think that, perhaps due to increased airflow, the water on the second floor does evaporate more than the water in the basement,” or “I think that, perhaps due to the tree blocking the sun, the air under the tree really is cooler than the air out in the open.”
If in general your hypothesis is true, then, using deductive reasoning, what specific, measurable results would you expect to observe as a consequence of testing your hypothesis? What is your prediction? For example, “If it is true that water evaporates more quickly on the second floor (if my hypothesis is true...) and I place a measured amounts of water in bowls in each location (if I do xxx...) then I should be able to see differences in the amounts of water that remain in the various bowls (then I should see xxx... results).
Develop an experiment to test your hypothesis. What would you do – what steps would you perform to see if you get your predicted results? What equipment and/or supplies would you need? What specific numbers/data would you need to gather, and how would you go about gathering and analyzing those data? What would be your control group? What ONE factor will be varied in your experimental group? How much repetition/replication do you need to have (one individual test subject does not make a group)? What sorts of statistics (like an average?) would be needed?
Determine what equipment and materials you will need. Very carefully and specifically think through what steps you need to do to gather the desired data, and describe these steps. For example, do not just say something like “I’m going to see which food these dogs like best.” What foods will be tested? How will they be offered to the dogs? What will you count or measure to have actual, numerical data to support your point – will you weigh the food before and after or will you count the number of times a dog goes to each type of food or what? Also, it really is not enough to observe just one dog’s behavior: suppose that dog has some illness or strange food preference. Repetition is important, and you need at have least three (or more) different tests (in this case three or more dogs, all presented with the same foods in the same manner) in each of your groups. What is your control group (the one with “normal” conditions – at least 3 trials)? What is your experimental group (what conditions – at least 3 trials)? Are you sure that only ONE variable at a time is being altered, is different between your control and your experimental group? For example, if you’re testing the effects of temperature on something, then you must make sure that light (strength, color, and duration), humidity, time, and any other factors remain identical among all subjects tested.
If you are a registered student, submit this much of your work so that I can check it and make sure you’re on the right track before you actually do anything.
Once I’ve seen and OKed your plan, actually do your experiment, record your data, do your calculations, and see what sorts of results you actually get. If the actual data you collect are not what you were expecting to get, that’s OK – finding out new things is what science is all about! If your data are not what you expected, record them, anyway, and don’t be tempted to “fudge it” to try to make things look “right.”
Based upon your data, what conclusions can you draw? Think about and try to explain what your results would indicate – make sure any claim you make is backed up by and based on the data which you collected. Any experiment has a number of possible outcomes, so if your data turn out differently than what you thought they would, think about what your data do mean. What possible factors/causes might account for that, and what possible alternate hypotheses might be posed to fit the actual data you collected? Do your results make you curious about any “spin-offs,” any other experiments you might like to do some day?
At this point, registered students should submit the rest of the assignment.

Grading Criteria

1. Background Thinking:

2	—	The observation was present and clearly stated
1	—	An observation was present, but vague and not clearly stated or not obviously related to the experiment
0	—	The observation was missing

2	—	The question was present and clearly stated
1	—	A question was present, but not clearly stated or unrelated to the experiment
0	—	The question was missing

2	—	The hypothesis was present and clearly stated
1	—	An hypothesis was seemingly present, but not clearly stated or not really an hypothesis and/or unrelated to the experimental procedure
0	—	The hypothesis was missing

2	—	The prediction was present and clearly stated
1	—	A prediction was seemingly present, but not clearly stated or not really a prediction
0	—	The prediction was missing

2	—	The prediction was correctly based on and derived from the hypothesis and proposed experiment
1	—	The prediction was only partially related to the hypothesis and procedure
0	—	The prediction was unrelated to the hypothesis and procedure, and thus, wasn’t really a prediction

2. Methods and Materials:

2	—	The procedure was clearly thought-out and stated
1	—	The procedure, as given, was somewhat vague or confusing
0	—	The procedure was missing or was so vague/confusing that it was very difficult or impossible to understand

2	—	Both a control group and an experimental group were specified
1	—	One or the other group was missing
0	—	Both the control and experimental groups were missing

2	—	There was adequate replication/repetition – 3 or more test subjects in both the control and experimental groups
1	—	There was some replication, although not enough – less than 3 test subjects in one or the other group
0	—	There was no replication – only 1 test subject in all of the “groups”

2	—	There only one variable – everything else was the same in both the control and experimental groups
1	—	Some variables were overlooked and, unintentionally, not carefully controlled
0	—	There was too many planned variables

2	—	The data to be gathered and methods of gathering them were clearly explained
1	—	The data and methods of measuring them were partially missing or were explained in a vague and confusing manner
0	—	The data to be gathered were not specified

2	—	The means of analyzing the data were clearly stated and explained
1	—	The explanation of the data analysis was vague and confusing or partially missing
0	—	The data analysis was not specified

2	—	All needed equipment and supplies were specified/included
1	—	While some of the equipment/supplies were given, other necessary items were missing and/or unnecessary items were included
0	—	Much/all of the necessary equipment/supplies were not specified or most of the items included were unrelated to the experiment

2	—	Where necessary, the author gave supporting reasons to justify the proposed procedure to be followed
1	—	It was not always clear why certain steps were being performed
0	—	The reasoning behind the procedure was missing – it was not at all clear why this procedure was being followed

3. Data:

2	—	All of the actual data collected were included
1	—	Some of the necessary data were missing or appeared to be fictitious
0	—	No data were presented or all alleged data appeared to be fictitious

2	—	The data were presented in a logical, organized manner
1	—	The presentation of the data was somewhat confusing or redundant
0	—	Data were seemingly present, but presented in an unintelligible, confusing manner

2	—	A valid analysis of the data (averages, etc.) was done, was included, and was clearly presented
1	—	Some data analysis that should have been included was not
0	—	No evidence of data analysis was presented/included

2	—	All units and measurements were given in the metric system
1	—	A mixture of English and metric system units was used
0	—	All measurements were given in English system or units were never given and it was unclear what system was being used

2	—	All numbers were clearly labeled with units
1	—	The units for some numbers were not specified, and/or it was unclear what some numbers represented
0	—	Most/all of the numbers were unlabeled and it was unclear what they represented

4. Conclusions:

2	—	Conclusions were drawn from the experiment that was done
1	—	Some “conclusions” were included that are merely restatements of portions of the data
0	—	No conclusions were drawn from this experiment

2	—	The conclusions were based upon and supported by quotes of the actual data
1	—	Some of the “conclusions” are merely repetitions of the data and/or conclusions are presented without being backed up by data
0	—	The “conclusions” were not based on the data, and some/all of them are the opposite of what the data indicate

2	—	The conclusions that were reached were reasonable for the data that were obtained
1	—	Some of the “conclusions” were unreasonable and far-fetched for the data that were obtained
0	—	The “conclusions” were totally speculative or in opposition to the data

2	—	It is obvious that much careful thought was given to the validity of the experiment and any possible flaws in the experimental design
1	—	Adequate thought was given to possible flaws in the experimental design
0	—	Little or no thought was given to possible problems with the experimental design

2	—	This experiment obviously piqued the author’s curiosity and generated much thought regarding further questions and experimentation
1	—	Adequate thought was given to further questions and future experiments
0	—	No curiosity was evident – little or no thought was given to possible further study

5. Overall Effort and Thought:

2	—	Each section contained only material appropriate to that section (no data in Methods and Materials, etc.)
1	—	There were a few cases where something was in the wrong section
0	—	Much material was presented out-of-order, in the wrong section

2	—	The student, obviously, went beyond the minimum requirements of the assignment
1	—	The student adequately completed the assignment
0	—	The student completed considerably less of the assignment than what was required

2	—	It is evident that the student used much insight, thoughtfulness, and critical thinking when completing this assignment
1	—	The student adequately thought about the assignment – there was, perhaps, a bit of “fuzzy thinking” in a couple places
0	—	The assignment gives the appearance of being “slapped together” just to get it done, with little evidence of thoughtfulness