1. Types of Descriptive Research
The Case Study
The Survey
Naturalistic Observation

2. The Case Study Where one person (or situation) is observed in depth.
What are the strengths and weaknesses of using a tragedy like the Columbine School Shootings as a case study?

3. The Survey Method
Used in both descriptional and correlational research.
Use Interview, mail, phone, internet etc…

4. The Survey Method What is good about a survey?
cheap, anonymous, diverse population, and easy to get random sampling
a sampling that represents your population you want to study

5. Random Sampling

6. Why do we sample? One reason is the False Consensus Effect:
the tendency to overestimate the extent to which others share our beliefs and behaviors.

7. Survey Method: The Bad Low Response Rate
People Lie or just misinterpret themselves.
Wording Effects
How accurate would a survey be about the frequency of having to use a plunger?

8. Naturalistic Observation
Observing and recording behavior in natural environment.
No control- just an observer.
What are the benefits and detriments of Naturalistic Observation?

9. Correlational Research
Detects relationships between variables.
Does NOT say that one variable causes another.
There is a positive correlation between ice cream and shark attacks. Does that mean that ice cream causes shark attacks?

10. Measured using a correlation coefficient.
A statistical measure of the extent to which two factors relate to one another

11. How to Read a Correlation Coefficient

12. Scatterplots
Perfect positive
correlation (+1.00)
Scatterplot is a graph comprised of points that are generated by values of two variables. The slope of the points depicts the direction, while the amount of scatter depicts the strength of the relationship.

13. Scatterplots
Perfect negative
correlation (-1.00)
No relationship (0.00)
The Scatterplot on the left shows a negative correlation, while the one on the right shows no relationship between the two variables.

14. Correlational Research
Correlation is the relationship between two variables.
Positive correlation – both values increase
Negative correlation –
One variable increases, while the other decreases.
Correlational Coefficient – strength of the relationship
0= no relationship
+ or – 1 = perfect relationship
Examples: SAT scores and success in college; Red wine and heart attacks; Prejudice and age; length of marriage and hair loss, etc.

15. There is a moderate positive correlation of +0.63.
Scatterplot
The Scatterplot below shows the relationship between height and temperament in people.
There is a moderate positive correlation of

16. Correlation and Causation
OBJECTIVE 9| Explain why correlational research fails to provide evidence of cause-effect relationships.

17. Given random data, we look for order and meaningful patterns.
Order in Random Events
Given random data, we look for order and meaningful patterns.
Your chances of being dealt either of these hands is precisely the same: 1 in 2,598,960.

18. Order in Random Events
Given large numbers of random outcomes, a few are likely to express order.
Jerry Telfer/ San Francisco Chronicle
OBJECTIVE 11| Explain the human tendency to perceive order in random events.
Angelo and Maria Gallina won two California lottery games on the same day.

19. Disconfirming evidence
Illusory Correlation
The perception of a relationship where no relationship actually exists. Parents conceive children after adoption.
Confirming evidence
Disconfirming evidence
Do not
adopt
Adopt
Do not conceive
Conceive
OBJECTIVE 10| Describe how people form illusory correlations.
Michael Newman Jr./ Photo Edit

20. What do each of these show?
The bigger they are, the harder they fall.
The more you save, the less you spend.

21. Experimental Research
Explores cause and effect relationships.

22. Steps in Designing an Experiment
Hypothesis
Pick Population: Random Selection then Random Assignment.
Operationalize the Variables
Identify Independent and Dependent Variables.
Look for Extraneous Variables
Type of Experiment: Blind, Double Blind etc..
Gather Data
Analyze Results

23. Experimental Vocabulary
Independent Variable: factor that is manipulated
Dependent Variable: factor that is measured
Confounding Variables: factors that effect DV, that are not IV.
Experimental Group: Group exposed to IV
Control Group: Group not exposed to IV
Placebo: inert substance that is in place of IV in Control Group

24. Analyze Results
Use measures of central tendency (mean, median and mode).
Use measures of variation (range and standard deviation).

25. A Skewed Distribution
Are the results positively or negatively skewed?