Dependent Variable:
The data that is
collected in the
experiment, the
results. If the
hypothesis is correct,
then this depends on
the independent
variable.
Independent Variable = The ONE
thing that the research is manipulating
to observe its effect.
If I do X with the independent variable, then
dependent variable will happen.
Example: If I provide some plants with more
light than others, they will grow faster.
While observations are an important part of
science, they are not sufficient to “prove” or
disprove a hypothesis. Example: In medieval
times, it was believed that rotting meat created
flies. Flies were clearly observed on exposed
meat plenty of times. Therefore, people had
plenty of “evidence” to support this idea.
Francesco Redi did an actual experimental
procedure to test his hypothesis that flies came
from other flies, not from the meat.
Independent variable =
exposure to flies in the open
air.
Dependent variable = growth
of maggots (fly larvae) on the
meat.
Controls are needed to eliminate alternate explanations of experimental
results.
Suppose a researcher feeds an artificial sweetener to 60 lab rats and observes
that ten of them die. Can the scientist then say for certain the sweetener
caused the death?
The underlying cause of death could be the sweetener or something
completely unrelated. Other variables, which may not be obvious, may
interfere with the experimental design. What if the rats were simply not
supplied with enough food or water, or the water was contaminated, what
if some rats had a disease?
The researcher needs to eliminate all other possible explanations in order to
accept or toss out the hypothesis. One way to do this is to separate the rats
into two groups: one group receives the sweetener and one does not. The
groups are kept in otherwise identical conditions, and both groups are
observed same ways. Now, any difference in death rate between the two
groups can be blamed on the sweetener —and no other factor—with much
greater confidence.
Example – What NOT to do…
Hypothesis: If there is a good fertilizer applied to the
plants, then they will grow faster.
Procedure: Look at different plants and test the soil
for the levels of fertilizer.
Data: The biggest plant had the most fertilizer.
Conclusion: Hypothesis was correct.
WRONG!!
Example – A GOOD (valid) experiment…
Hypothesis: If I apply fertilizer X to the plants,
then they will grow faster than those without
fertilizer.
Procedure: Take 40 identical plants (same
species, age, size, soil, pots, amount of water)
and divide into 2 groups. Give 1st group a dose
of fertilizer once/week. Treat 2nd group
exactly the same – but do not give the
fertilizer. Measure growth every day for 4
weeks. Compare average growth rate in group
1 to group 2.
Data: Group 1 plants grew faster than group 2.
Conclusion: Hypothesis was supported by data.
YES!!!!
Now how do I design an experiment?
• Try to make a clear and SIMPLE hypothesis using
the format given here.
• Write a procedure that tests the hypothesis by
dividing up your subjects into groups and
treating the groups exactly the same
EXCEPT for the independent variable.
• ASK FOR HELP if you are lost! Your
teacher is more than happy to give
suggestions if you have an idea to start the
experiment!!!!