1. Research Methods in Psychology

2. Correlation
A statistical value of the relationship between two variables
Positive Correlation
As one number increases, the other increases.
Ex: Study time to GPA
Negative Correlation
As one number increases, the other decreases.
Ex: Absences to GPA
No Correlation
Variables do not affect one another in a significant way
Ex: Height to GPA

3. Correlation Coefficient
Ranges from to 1.00
Zero is no relationship
-0.85 is a stronger relationship than .34
CORRELATION IS NOT CAUSATION!!
(i.e. Just because two variables have a correlation does not mean one causes the other)

4. CORRELATION IS NOT CAUSATION!!!
People that floss everyday live 3 years longer than those that do not.
Red wine drinkers live longer than those that do not drink red wine.
As speed limits increased on America’s highways, the death rate went down.
Women with breast implants commit suicide 3 times as often as those without breast implants.
Children who are played Mozart in the womb have higher IQ’s.
Marijuana users in youth are more likely to have mental illness as adults.
As ice cream sales increased, so did shark attacks.
More TV’s per person in a country, the longer people live.

5. Illusory Correlation 5

6. The Experiment
Only research method capable of showing cause and effect

7. Experimental Method Review Literature of Past Research
Formulate Hypothesis
Design Research/Study Method (naturalistic observation, case studies, surveys, experiments, etc)
Collect the Data
Analyze the Data
Report the Findings (journal, critique, replicate)
Draw Conclusion or Theory on Explanation of Findings

8. Hypothesis
A statement about the relationship between two or more variables
Must be testable and refutable
Instead of proving the hypothesis, science usually tries to disprove a null hypothesis.
Null Hypothesis (H0):
opposite of hypothesis
Statistical Significance :
95% not due to chance
Hypothesis Example:
H1: Gender has an effect on spatial ability
H0: Gender does not have an effect on spatial ability

9. Variables Independent Variable (I.V.): manipulated by experimenter
Dependent Variable (D.V.): MEASURED variable influenced by independent
Operational definition
Confounding/extraneous variables

10. Control Group No treatment or placebo Serves as basis for comparison
Serves to eliminate alternative explanations

11. Population – The larger group of people from which a sample is drawn
Sample: Representative of the population
Two ways to get sample
Random: Every member of the pop has = chance
Stratified: Sample is put together by picking a
group statistically equal to the population

12. Control Measures Counterbalance: controls for order effects
Single-Blind: subject unaware of assignment
Double-Blind: subject and experimenter unaware of placement
Randomization
From population (sample)
From assignment to groups (assignment)

13. Other Research Methods
Ex Post Facto (after the fact)
- Independent variable already present
- Not a true independent variable, no cause and effect
- Often used due to ethical concerns
Naturalistic Observation
- Natural setting: behavior is not interfered with or altered
Survey Method
- Gathers data on attitudes and behaviors.
Case Study
- Intense study of an individual

14. Flaws in Research Sampling Bias Overgeneralization Placebo effect
Hawthorne/Barnum effect
Demand Characteristics
Experimenter Bias

15. STRENGTHS AND WEAKNESSES OF
Evaluating Research
STRENGTHS AND WEAKNESSES OF
Experiment
Correlation
Surveys
Naturalistic Observation
Case Studies

16. Ethics in Research Participants are free to withdraw at any time
No undo stress
Subjects informed of significant factors that may influence their willingness to participate
Subjects should be debriefed
Ethical treatment of animals
Generally research goes before a review board for approval

17. Statistics Descriptive Statistics Organize and summarize data
Central Tendency: mean, median, mode
Standard deviation: variation in data
Range: distance from smallest to largest
Inferential Statistics
Interpret data and draw conclusions
Used to test validity of hypothesis (t-test)

18. Standard Deviation

19. Statistical Significance
Probability results are due to chance
Inferential stats (t-test) are used to check for either a 5% (p<.05) or 1% (p<.01) level of significance.
Lottery tickets 14, 3, 27, 41, 18
1, 2, 3, 4, 5
Coin flips HHHHHHH or HHTHTHT
More likely?

20. Bell or Normal Curve 68% are within One standard deviation from mean
95% are within Two standard deviations from mean

21. Measures of Central Tendency
A Skewed Distribution

22. Skews