Hans the horse appeared to be able to do math and answer questions correctly, but was actually just picking up on subtle body language cues from his owner. When the owner was hidden from view, Hans could no longer answer correctly. This story illustrates the importance of controlling for confounding variables in methodology. Psychologist Oskar Pfungst discovered that Hans' ability to answer questions depended on receiving unconscious cues from his owner, rather than any real intellectual ability.

1. Sampling
• Identify the
population you want
to study.
• The sample must be
representative of the
population you want
to study.
• GET A RANDOM
SAMPLE.
• Stratified Sampling

2. • Clever Hans the horse could do simple math and spell out the answers to simple
questions. He wasn’t always correct, but he was most of the time.
• While a team of scientists, veterinarians, zoologists and circus trainers could not
figure out how Hans was correctly answer the questions, Oskar Pfungst, a
psychologist did. What did he discover?

3. • While Hans could not do math or correctly answer questions on his own,
he was very perceptive.
• Hans was picking up on subtle body language given off by his owner who
asked the questions.
• When the owner was hidden from view, suddenly Hans could not answer
the questions correctly.
• How does this story relate to methodology?

4. Hypothesis
• Expresses a
relationship between
two variables.
• A variable is anything
that can vary among
participants in a
study.
• Participating in class
leads to better
grades than not
participating.

6. Independent Variable
• Whatever is being
manipulated in the
experiment.
• Hopefully the
independent variable
brings about change.
If there is a drug in an
experiment, the drug
is almost always the
independent variable.

7. Dependent Variable
The dependent
variable would be the
effect of the drug.
• Whatever is being
measured in the
experiment.
• It is dependent on
the independent
variable.

8. Operational Definitions
• Explain what you
mean in your
hypothesis.
• How will the variables
be measured in “real
life” terms.
• How you
operationalize the
variables will tell us
if the study is valid
and reliable.
Let’s say your
hypothesis is that
chocolate causes
violent behavior.
• What do you mean by
chocolate?
• What do you mean by
violent behavior?

9. Experimental Method
• Looking to prove
causal relationships.
• Cause = Effect
• Laboratory v. Field
Experiments
Smoking causes health issues.

10. Beware of
Confounding Variables
If I wanted to prove that
smoking causes heart
issues, what are some
confounding variables?
• The object of an
experiment is to prove
that A causes B.
• A confounding variable is
anything that could cause
change in B, that is not
A.
Lifestyle and family
history may also
effect the heart.

11. Random Assignment
• Once you have a
random sample,
randomly assigning
them into two groups
helps control for
confounding variables.
• Experimental Group v.
Control Group.
• Group Matching