1. Experimental Design

2. A claim, prediction, testable. Is this a good hypothesis?
Step One:
Hypothesis:
A claim, prediction, testable.
Is this a good hypothesis?
“Do bright colors cause people to be happy and pastel colors cause people to be sad?

3. Is this a better hypothesis?
“Studying in a brightly
colored room will increase
happiness in college students.”

4. Developing an Operational Definition
Step Two:
Developing an Operational Definition
State each variable in specific terms in order for experiment to successfully be repeated.
Which variables will need to be operationally defined? (operational definitions)
“Studying in a brightly colored room will increase happiness in college students.”
Independent Variable: Manipulated
Dependent Variable: Measured

5. People: College Students 18-22
Brightly Colored Room: A Red Room
Happiness: Number of times a student smiles, or score on a mood inventory survey
Other Variables?

6. Experimental Design Manipulate Measure Analyze
Hypothesis
A claim, prediction, testable.
Identify (IV) (DV)
Operationally define the variables (important for replication)
Choose (Random Selection)
Choose a representative sample.
Random Assignment
Control Group (no treatment, placebo)
Experimental Group (receives treatment; IV)
Manipulate
(Treatment, no treatment, Placebo, Double-Blind Procedure)
Measure
Compare different Conditions (Control & Experimental)
Analyze
Statistical procedures and conclusion
Statistically Significant?
Hypothesis: An educated guess based stated in a precise manner.
Example: Ritalin will decrease negative classroom behavior of children diagnosed with ADHD.
IV-variable that is manipulated or controlled.
Example: drug dose, various levels of dose, placebo
DV- measurement of subjects behavior that depends on the IV.
Example: Measurement of child’s behavior depending on the condition he was in
Random Selection: each participant in a sample population has an equal chance to participate.
Experimental Group-receive treatment (drug)
Control Group-don’t receive treatment…but all else is same
Statistical Procedures are used to determine whether differences observed in dependent variables (behaviors) are due to independent variables (treatment) or to error or chance occurrence.