Assignments » Writing Hypotheses|
Purpose: to learn how to write testable, measurable, scientific hypotheses.
Most students believe that they are conducting an experimenting anytime they are given a laboratory assignment in science. However, more often than not, students are doing something other than a true scientific experiment. This is not necessarily bad. A good deal of science is about making observations and describing what we see. For example, a study of biodiversity in an ecosystem usually involves looking at wide variety of specimens and maybe sketching and recording their unique characteristics.
However, there are other times when we science teachers are trying to teach you--the students--how scientists work. It is critical that students learn how to verify the claims of others. In order to learn about what is not known or to verify a notion, scientists use the so-called "scientific method". When we want to answer a question or verify something in class, the "scientific method" might be used and an actual experiment may be conducted. It does not matter that the experiment has been done a thousand times before or that your teacher already knows the results. What matters is that you don't know the results and that you can independently find a verifiable answer.
In real experiments, real hypotheses should be written before the actual experiment. Do you know what a real hypothesis looks like? Do you know how to write one?
What Is a Real Hypothesis?A hypothesis is a tentative statement that proposes a possible explanation to some phenomenon or event. A useful hypothesis is a testable, measurable statement which may include a prediction. A hypothesis should not be confused with a theory. Theories are general explanations based on a large amount of data. For example, the theory of evolution applies to all living things and is based on wide range of observations. However, there are many things about evolution that are not fully understood, such as gaps in the fossil record. Many hypotheses (high-poth-uh-sees) have been proposed and tested, and some of them have not been supported by the data. But the THEORY of evolution is still strongly supported by the bulk of scientific evidence and is widely accepted in the scientific community.
When Are Hypotheses Used?
The key word is testable. You will need to write a hypothesis whenever you plan to perform a test of how two things might be related. This is when you are doing a real experiment, and not just demonsatrting an idea or a process. You are testing the relationship between variables.
Usually, a hypothesis is based on some previous observation, such as noticing that in November many trees undergo color changes in their leaves and the average daily temperatures are dropping. Are these two events connected? How?
Any laboratory procedure you follow without a hypothesis is really not an experiment. It is just an exercise or demonstration of what is already known.
How Are Hypotheses Written?
For this assignment, we will be focusing on the 6 statements below. You might want to write them down or you can copy and paste them into a Word document so you can play around with them.
- Chocolate may cause pimples.
- Salt in soil may affect plant growth.
- Plant growth may be affected by the color of the light.
- Bacterial growth may be affected by temperature.
- Ultra violet light may cause skin cancer.
- Temperature may cause leaves to change color.
All of these statements are are examples of hypotheses. However, their form is not particularly useful. Notice that they all include the tentative word "may". Using the word "may" leaves open the option that the experimenter also acknowledges that the opposite could also be true (chocolate may NOT cause pimples). Which idea is really going to be tested in the experiment? WHile each statement above is technically a hypothesis, none of them are testable, measurable, scientific hypotheses.
Let's compare the statements above with some other types of statements. If we say "Trees will change color when it gets cold." then we are making a prediction. Or if we write, "Ultraviolet light causes skin cancer." then we could be writing a conclusion (which comes at the end of an experiment, after you've gathered the data). So how do you write a scientific, testable, measurable hypothesis? One way to improve your hypothetical statements is to formalize the form of the hypothesis using either of the two methods shown below.
Formalized Hypotheses Technique #1: "If this is related to that, then prediction..." Method
Look at the two examples of hypotheses below:
"If skin cancer is related to ultraviolet light , then people with a high exposure to uv light will have a higher frequency of skin cancer."
"If leaf color change is related to temperature , then exposing plants to low temperatures will result in changes in leaf color."
Notice that both of these statements contain the words "if" and "then". These words are necessary in a formalized hypothesis. almost all hypotheses you write for our class will use the "If... then..." format.
But not all if-then statements are hypotheses! For example:
"If I play the lottery, then I will get rich."
This is a simple prediction. It is NOT a hypothesis.
In a formalized hypothesis, a tentative (possible) relationship is stated. For example, you might think that the frequency of winning is related to frequency of buying lottery tickets. This "if" statement would be followed by a "then" statement. The word "then" is followed by a prediction of what will happen if you increase or decrease the frequency of buying lottery tickets. If you always ask yourself how one thing is related to another, then you should be able to test it.
Formalized hypotheses contain two variables. One is "independent" and the other is "dependent." The independent variable is the one you, the "scientist" control or manipulate. It's what I like to call the "I change" variable; as the scientist, it's the thing that I'm changing or messing with (or manipulating) in the experiment! The dependent variable is the one that you observe and/or measure; it's the ddata and rresults that you intend to collect (the doctor/DR variable). The dependant (responding) variable depends on how you manipulate the independent variable.
In the statements about skin cancer and leaf change above, the dependent variable is identified in blue and the independent variable is identified in red (at least in the simplest of terms). While it doesn't really matter which goes first, most scientists state the dependant variable first, followed by the independent variable.
But be careful! If I asked you to clearly state the independent variable in the statement about leaf color, I would expect you to say more than just "temperature." While the temperature is certainly part of the independent variable, I expect you to tell me what about the temperature is being varied! We can infer that in an experiment testing this variable, some trees might be exposed to low temperatures, while other trees might be exposed to warmer temperatures. If I were to clearly state the independent variable, it would be "whether each tree is exposed to low temperatures or warmer temperatures." If I was REALLY being scientific, my hypothesis would even give the precise range of temperatures to which the trees would be exposed.
The ultimate value of a formalized hypothesis is it forces us to think about what results we should look for in an experiment. Of course, the strongest hypotheses also include a measurable prediction. More on THAT in just a minute!
Formalized Hypotheses Technique #2: "If this independent variable is compared to that independant variable, then dependant variable/prediction..." Method
This next way of constructing a hypothesis might look something like this:
"If some subjects experience high exposure to UV light while others avoid UV exposure, then the subjects with high exposure to UV light will have a higher frequency of skin cancer than those who avoid UV exposure."
"If deciduous trees that have been exposed to gradually cooling temperatures and deciduous trees that have only been exposed to warmer temperatures are observed over several months during the fall season, then a change in leaf color will be observed only in the deciduous trees exposed to the gradually cooling temperatures, and not in the deciduous trees exposed only to warm termperatures."
Basically, in this method, the "if" part of your statement should summarize the different conditions or scenarios being compared (your independent variable), and the "then" part of your hypothesis should summarize what you intend to measure (the dependant variable) and include a measurable prediction.
A strong scientific hypothesis not only uses one of the two formalized methods shown above, but it should also include a measurable prediction about the results. Basically, this means that when you write a hypothesis, you want to avoid using phrases like:
- better than
- bigger than
- a little more than
- greater than
- faster than
- will occur more often than
All of the phrases above are subjective; that means they are open to interpretation. You might predict that "a lot" of trees exposed to cool temperatures will change colors. But what exactly does "a lot" mean? Since everyone might not agree what "a little" or "a lot" really means, then your data might be interpreted differently by different people.
Let's look at some examples:
"If skin cancer is related to ultraviolet light , then people with a high exposure to uv light will have a 25% higher frequency of skin cancer than those not exposed to uv light."
"If leaf color change is related to temperature , then exposing plants to low temperatures will result in changes in leaf color in 85% of deciduous plants."
To make your prediction measurable, you are basically enhancing words like "a little" or "bigger" or "more than" with real numbers. By adding a value to your prediction, you provide a measure of HOW MUCH effect you expect your independent variable to actually have on the dependant variable. A low percentage or number in your prediction usually indicates a weak relationship between the independent and dependent variables. A larger number or percentage in your prediction indicates that you think the independent variable has a big influence on the dependant variable.
Including a measurable, quantifiable prediction in a hypothesis can be difficult if you know little or nothing about the system you are investigating. That's why RESEARCH is an important step in the scientific method. Students often forget that research must be started before you conduct your experiment. Without research, it's pretty hard to write a formalized, measurable, testable, scientific hypothesis. It's another reason why scientists often refer to a hypothesis as an educated guess!
Assignment Grade: "Writing Hypotheses"
In a Word document (make sure you add your heading), rewrite the first four hypotheses in the original list at the top of the page using each of the formalized styles shown above. Try to include a measurable prediction as well (you could use italics to show your prediction). Finally, write an original hypothesis of your own using each of the two methods you read about. You should have 10 hypotheses total when you are done (don't forget to make up one on your own and write it using both methods). When you are done, make sure you print your work and turn it in.
Here's the original list of hypotheses that need to be formalized:
- Chocolate may cause pimples. (done in class)
- Salt in soil may affect plant growth. (done in class)
- Plant growth may be affected by the color of the light.
- Bacterial growth may be affected by temperature.
Ultra violet light may cause skin cancer. Temperature may cause leaves to change color.
Examples from our class discussions on Tuesday:
If a person’s frequency of pimples is related to the amount of chocolate a person consumes, then the frequency of pimples will be 25% higher when subjects consume large amounts of chocolate (5 Hershey bars per day) than when subjects consume little or no chocolate.
If subjects consume chocolate as part of their daily diet (5 Hershey bars per day for 4 weeks) and then abstain from for the same amount of time, then subjects will experience a 25% decrease in the frequency of pimples while abstaining from chocolate compared to when their diet included daily consumption of chocolate.
Gifted Science with Mrs. Flynt
Gifford Middle School, Indian River County, Florida
4530 28th Court