1. Research Methods

2. Samples Whole population studies are impractical
Sample: group selected from a given population that represents that population
Population: All football players at Ohio State University
Sample: 10 players from the team

3. Samples
Random Sample: all members of a population have an equal chance
Might choose to get a list of all the players & their jersey numbers, keep pulling numbers out of a hat until you have 10 players that are willing to participate.
Stratified Sample: sample matches proportions of the population
If 30% of the team has a 3.5 GPA or higher, make sure 30% of your sample does too.

4. Surveys Subjects are asked a fixed set of questions
May be written (questionnaire) or verbal (interview)
Questionnaires help avoid researchers from impacting the results as much as they could with interviews

5. Surveys
Also need to be concerned about volunteer bias: those who participate often have a different opinion than the general population.
Ex. When calling people at dinner to ask how the president is doing, typically only the people who hate him will stay on the phone to rant. (the ones who think the president is “fine” want to get back to dinner)

6. Case Study Intense study on one or more participants
Great for generating new hypotheses.
Poor for proving/disproving anything
You typically cannot generalize your results to other people

7. Longitudinal Study
Same group of subjects are studied over the course of a number of years to see how characteristics change (or not) with development
Ideal for explaining the impact of development on individuals.
Extremely expensive, time consuming, and potentially useless (if subjects disappear)

8. Cross Sectional Study
Subjects are organized into age groups, each group is tested the same, results show the impact of age/development on behavior.
Much faster and cheaper than a Longitudinal Study

9. Naturalistic Observation
Method where the subject is observed in a natural setting
Ex. Go watch apes in the jungle, freshmen in the cafeteria.
Researchers need to avoid disturbing the subject to avoid tampering with results.

10. Laboratory-Observation/Testing
Observing how subjects behave in a controlled environment
Ex. For small children, observing how they handle a building block test can provide information on that child’s development

11. Analyzing Data With one piece of data, use mean, median, mode, etc.
Intelligence Quotient (IQ)

12. Analyzing Data
With two pieces of data, we try to see if there is a correlation (how close one thing relates to another)
Ex. “Does income correlate with the number of years of college someone completes?”
Positive Correlation: as one measure increases, so does the other
Negative Correlation: as one measure increases, the other decreases

13. Analyzing Data
Positive Correlation: as one measure increases, so does the other
Ex. “As a person’s height increases, their weight usually increases too”
Negative Correlation: as one measure increases, the other decreases
Ex. “As a person’s stress level increases, their immune system function decreases”

14. Experiments
Controlled studies where psychologists can focus on only the variables they want to study.
Only experiments allow us to make a conclusion of causation: A change in one thing causes a change in another.
True psychologists will also replicate (repeat over and over) their study

15. Experiments
Independent Variable (IV): variable being controlled to change results
Dependent Variable (DV): variable that is changed based on a change to the IV
Example: How does the amount of sleep a student experience impact their score on an IQ test?
IV: The amount of sleep the subject experiences
DV: The subject’s score on an IQ test

16. Experiments (cont.)
Typically, researchers need to have at least two groups:
Experimental group: group that experiences the change in the Independent Variable (IV)
Control group: treated the same way as the ex. group., but their Independent Variable is not changed.
Example: How does the amount of sleep a student experience impact their score on an IQ test?
Experimental group: 10 students are woken after only 2 hours of sleep and given the IQ test
Control group: 10 students are woken after 8 hours of sleep and given the IQ test

17. “Blind” Experiments
Unless properly accounted for, both the subjects and the researchers can impact results. This is accounted for with “blind” experiments.
Double-blind: neither the subjects nor the researchers know which people are in the experimental group and which are in the control group.
A second researcher/team is brought in to organize the entire study
When studying medicines, you typically want to give the control group a placebo (sugar pill) so they don’t know they aren’t getting the medicine.

18. “Blind” Example
Research Question: How does the amount of sleep a student experience impact their score on an IQ test?
IV: The amount of sleep the subject experiences
DV: The subject’s score on an IQ test
Experimental group: 10 students are woken after only 4 hours of sleep and given the IQ test
Control group: 10 students are woken after 8 hours of sleep and given the IQ test
Double Blind set-up: Participants do not know whether they will be woken in 4 hours or 8 hours. The researchers giving the IQ test are not told which students were woken after 4 hours and which were woken after 8 hours