Inductive reasoning (from the particular to the general) to
generate a testable hypothesis
Deductive reasoning (from the general to the particular) to
generate predictions about future observations
Tests of the predictions with controlled experiments or
observations
Logically interpret the results – conclusions
Start over again with the new observations added to the old
observations
Hypotheses
Can never be proven true, only disproven
Any set of observations can be explained by many hypotheses
Ocham's razor (the explanation that requires the fewest
assumptions is preferred)
Must explain all known observations
Must be testable
Must be based on logic and natural processes
Hypotheses that have withstood many tests and explain many
observations are called theories
Hypotheses
Theories
A postulate for a specific investigation; a statement
tested by experimentation
Hypotheses that have been repeatedly tested and have not
yet failed
The tentative answer to a scientific question
Hypotheses that explan many diferent observations and makes many different
predictions
An Example
Observations
Marsh grasses in different locations grow at different rates and to different
heights.
Questions
What causes the difference in growth rate and height?
Inductive Generalization
A large number of observations on growth in marsh grasses
and other plants suggest some specific questions
Amount of nutrient – Nitrogen (N), Phosphorous (P) or Potassium
(K)?
Tidal flow or depth?
Activity of mud-dwelling animals?
Hypothesis
A postulated answer to the question
An increase in N levels causes an increase in growth and
height
Null form: an increase in N levels has no effect on growth
A null hypothesis is the hypothesis that something is not the answer – the
null is very useful because while you can not prove anything true, you
can prove things false
Hypotheses lead to deductive predictions
If the growth and height of marsh grasses is increased by
increased N levels, then grasses with added N should have
greater growth and height.
Deductive arguments are tested. (by Experiment or Observation)
Experiment
How to test the hypothesis - What data - How many repeated
tests - etc.
Decision - paired plots: start with two nearly identical plots
Then add Nitrogen to one of the plots only (randomly chosen,
of course) and measure the effect of the added Nitrogen on the
growth of the grass. If the hypothesis is true then the plot with
N added will show more growth
Experimental Variables:
Independent: to be varied by investigator = N level
Dependent: growth rate, height
Controlled Variables:
many - water depth; soil organisms; salinity; other
nutrients; etc.
try to assure that paired plots are as much alike as
possible
Experimental Design
Preferred test is a controlled experiment
Only one independent variable is changed at a time
All other independent variables are held constant (controlled)
usually can not control all independent variables so
control all variables that you believe are relevant
Must be reproducible
this checks for other unknown variables and stochastic
effects
Usually have an alternate hypothesis and a null hypothesis
try to prove that one or the other is false
can only have statistical proof (95%)
When using humans you need to control for bias
Double-blind randomized trials
experimental subjects are assigned to control and
experimental groups randomly
use a placebo for the controls
subjects do not know whether they recieve the treatment or
the placebo
researcher does not know whether they recieve the treatment
or the placebo until after the results have been analysed
If a controlled experiment is impossible,
then use controlled observations
Some examples
big things: planets, stars, etc.
things that take a long time: evolution, geology, etc.
unique events: origin of life, the universe, earthquakes,
etc.
expensive or dangerous events: toxic waste spill, nuclear
melt down, etc.
Try to control for all relevant variables
Must predict the result of new observations
Assignment due before next class meeting:
After reading the class notes on designing experiments, think about some example
of pseudoscience or alternative science (astrology, palm-reading, accupuncture,
intelligent design, echinacea, etc.) you've heard about, come up with a scientific
hypothesis based on the idea and then design an experiment that could be done
to test the hypothesis. Your experiment
should have a clear question, a hypothesis, a prediction, and an experimental
design that would test your prediction.
This document is maintained by: Jeff Bell
Last Update:
Tuesday, July 11, 2006