Hypothesis Formation in Epidemiology FAQ
These FAQs will assist you as you complete this task about forming good, testable hypotheses.
What is a hypothesis?
A hypothesis is a tentative answer to a well-formed
question. Modern scientists commonly follow a five-step
process (known as the scientific method) when pursuing a
problem or developing a theory. (1) They make an
observation. This might be some phenomenon the scientist
ran into by accident, but more often it will be something he or
she observed while studying a problem. (2) They ask
questions about the observation(s). (3) They form a
hypothesis—a tentative answer to a question. (4) They make
predictions based on the hypothesis. (5) They test the
predictions.
What is a scientific
hypothesis?
If a hypothesis can’t give rise to predictions that could be tested
and found false, it is not a scientific hypothesis. In principle,
any scientific hypothesis is subject to testing and falsification. If
no evidence could conceivably disprove it, a hypothesis is not
scientific. Interestingly, hypotheses cannot be proven to be
correct. They can continually be challenged by some new test
or piece of evidence proving them to be false.
How do I create a hypothesis?
A hypothesis begins with a question—the hypothesis is a
tentative answer or explanation that addresses the
question. Suppose you are looking for something in the dark,
using a flashlight. Your flashlight goes out. Your question is
almost certainly “Why did the flashlight go out?” Stop and think
for a moment… can you create one or two hypotheses (answers
to your question)?
One reasonable hypothesis would be: The batteries are
dead. Another reasonable hypothesis would be: The bulb has
burned out.
Generate hypotheses by thinking of them as answers to
questions. Remember, though: A hypothesis is a scientific
hypothesis only if it could be tested.
What is an alternative
hypothesis?
The “alternative” hypothesis is a statement that you believe to
be true.
For example, let’s say you have a theory and you want to test it.
First, you come up with the alternative hypothesis, which is your
theory:
“An employer who has a screening process is more likely to hire
a quality candidate than an employer who just hires the first
person that asks him/her for a job.”
This hypothesis states the direction (e.g., more likely, less likely)
and tells the reader what you believe to be true.
What is a null hypothesis?
While it may seem counterintuitive, the unstated goal of any
study is not to prove the alternative hypothesis, but it is actually
to try to disprove the null hypothesis (as mentioned previously,
hypotheses cannot be proven to be correct).
In epidemiology, when a hypothesis is stated as the null, it says
there is no difference between group 1 and group 2. At the end
of a study, you find that the null is either not true and there is an
explanation for the difference between the two groups or you
find that the null is true and there’s no difference between the
two groups.
Here are examples of null hypotheses:
1. If you want to test whether more boys or girls at
Lakeview High prefer to drink Coke versus Pepsi, the
null hypothesis would be, “There is no difference
between the percentage of girls and the percentage of
boys who drink Coke instead of Pepsi at Lakeview
High.”
2. If you want to test whether students who listen to music
while doing homework have lower or higher GPAs, the
null hypothesis would be, “There is no difference in GPA
between those high school students who usually listen
to music while doing homework and those who rarely
listen to music while doing homework.”
In epidemiology, what makes a
hypothesis “good” (or
testable)?
There are two important keys to a good, testable hypothesis. It
must be simple and specific.
Simple – you should always test one variable at a time, not
multiple variables. If you try to include multiple variables in your
hypothesis, you won’t ever be able to determine the direct
association.
Example - If your alternative hypothesis states that smoking and
alcohol consumption both lead to heart disease, how will you
determine who falls into the “exposed” group (the group
exposed to the thing that leads to heart disease)? People who
smoke? People who drink? Or only people who smoke and
drink? It’s better to have two hypotheses, and to test each
separately. The first hypothesis could examine the relationship
between alcohol and heart disease and the second could
address the relationship between smoking and heart disease.
Specific – your hypothesis should be as specific as you can
make it. Whenever possible, you should include details that
indicate exactly what you are looking for in your study. For your
alternative hypothesis, this includes the direction of the
association (e.g., people who smoke are more likely to get lung
cancer; people who exercise regularly are less likely to get heart
disease).
Example - Let’s say you have a theory that people who drink
coffee have stomach problems. There are some additional
questions that need to be answered so your hypothesis is easier
to test:

How much coffee?
What are the steps in forming
a null hypothesis?

Compared to whom?

What kind of stomach problems?
1. Think of the question you want to research.
2. Turn the question into a statement that says what you
think to be true or what you hope to find out (alternative
hypothesis).
3. Make sure the hypothesis is both simple and specific.
4. Reframe the hypothesis and make it “null” by stating that
there is no difference between group 1 and group 2.