1.) *Experiment* 2.) Quasi-Experiment 3.) Correlation 4.) Naturalistic Observation 5.) Case Study 6.) Survey Research.

1.) *Experiment*2.) Quasi-Experiment3.) Correlation4.) Naturalistic Observation5.) Case Study6.) Survey Research

Research method in which investigator manipulates variable (independent variable) under carefully controlled conditions and observes whether any changes occur in second variable (dependent variable)

Most common procedure ◦ Why?

Independent Variable (IV)- Condition or event experimenter varies to see impact on another variable (dependent variable).

Dependent Variable (DV)- Variable thought to be affected by the manipulation of the independent variable. ◦ Outcome measure

Experimental Group(s)- Participants here receive some special treatment with regards to the independent variable

Control Group – Similar participants not receiving special treatment given to experimental group

***Want groups to be the same on everything except for independent variable***

Summary

Examples◦ Sample experiment studying effects of alcohol on

memory

◦ Sample experiment studying effects of coffee on sleep

Again want groups similar in every way except for IV◦ Why might this be difficult?

Extraneous variables (Confounds)- Any variable other than IV that seems likely to influence DV

Examples of possible confounds in research

How does research correct for possible confounds

Random assignment- All subjects have equal chance of being assigned to any group in study.

Advantages:◦ Cause and Effect◦ Control

Disadvantages:◦ Artificial◦ Can’t be used to study every question

An experiment done in a tougher situation◦ Groups naturally exist◦ Cannot do random assignment

Example situations

Research that studies the relationship between 2 variables.◦ Example studies

Relationship can be positive or negative Positive- Variables change in same direction; as

one increases, other increases◦ Example variables

Negative- Variables change in opposite direction; as one increases, other decreases◦ Example variables

Correlation Coefficient- A number computed telling how strong the relationship between two variables is.◦ Ranges from -1 to +1◦ Sign tells if relationship positive or negative

Positive (+) Negative (-)

# tells strength

Can be used for prediction

No cause and effect relationship◦ We cannot say one variable causes other◦ WHY?

Researcher engages in careful observation of behavior without intervention◦ Examples

What could you see as potential limitation?

In depth investigation of single subject or person◦ Thorough interviews, observation, testing

When is this typically done?

Researcher distributes questionnaires to gather information about specific aspects of individual behavior or background

Advantages

Disadvantages