1. RESEARCH METHODS

2. Research Strategies

3. Research Strategies
Descriptive—strategies for observing and describing behavior (answer who, what, when, where & how often)
Correlational methods
Naturalistic observation
Case studies
Surveys
Experimental—strategies for inferring cause and effect relationships among variables

4. Descriptive Study Describes a set of facts
Does not predict what may influence the facts
May or may not include numerical data
Example: measure the percentage of new students from out-of-state each year since 1980

5. Case Study
In depth study of one individual with the hopes of determining universal principles
This technique is very open to bias
Difficulty of applying data from one person to everyone
Generally used to investigate rare, unusual, or extreme conditions

6. Survey Method
Research method that relies on self-reports; uses surveys, questionnaires, interviews.
Usually a very efficient and inexpensive method
Watch out for Framing/Wording Effects – The way a question is worded can bias the answer.
Have to watch out what we take from polling information:
Also, people lie in surveys:

7. SamplingTerms
Population—large (potentially infinite) group represented by the sample. Findings are generalized to this group.
Sample—selected segment of the population
Random selection—every member of larger group has equal chance of being selected for the study sample
Random Sample – Results from random selection, each member of the population had an equal chance of being included.
If a sample is not random it is said to be biased.
Representative/Stratified sample—closely parallels the population on relevant characteristics
Watch this short clip on the difference between these. (3 min)

9. DAILY
DOUBLE

10. QUESTION Explain the difference between a random sample and a representative sample.
ANSWER:
Random sample—every member of larger group has equal change of being selected for the study sample
Representative sample—closely parallels the population on relevant characteristics

11. Naturalistic Observation
Method of observation where subjects are observed in their “natural” environment
Subjects are not aware they are being watched
Could use hidden cameras or two way mirrors

12. Meta-Analysis
Combining the results from multiple different research studies.
Example: Studying lung cancer from second hand smoke.

13. Bias
Situation in which a factor unfairly increases the likelihood of a researcher reaching a particular conclusion
Bias should be minimized as much as possible in research

14. Researcher Bias
The tendency to notice evidence which supports one particular point of view or hypothesis
Objectivity tends to reduce bias.

15. Participant Bias/ Hawthorne Effect
Tendency of research subjects to respond in certain ways because they know they are being observed
The subjects might try to behave in ways they believe the researcher wants them to behave
Can be reduced by naturalistic observation

16. Critical Thinking
Thinking that does not blindly accept arguments or conclusions but questions their validity
Need to do this to avoid bias

17. Longitudinal and Cross-Sectional Studies

18. Developmental Psychologists
Psychologists who study how individuals change throughout their lifetime

19. Longitudinal Study
Developmental study where researchers study the same group of individuals for many years
Can be very expensive and difficult to conduct

20. Cross-Sectional Study
Developmental study where researchers simultaneously study a number of subjects from different age groups and then compare the results
Cheaper, easier than longitudinal studies, but group differences may be due to factors other than development.

21. Longitudinal/Cross Sectional Study

22. Correlational Study
Collects a set of facts organized into two or more categories
measure parents’ disciplinary style
measure children’s behavior
Examine the relationship between categories
Correlation reveals relationships among facts
e.g., more democratic parents have children who behave better

23. Correlational Study
Important NOT to imply a cause and effect relationship between the variables
Correlational study does not determine why the two variables are related--just that they are related.
Correlational studies are helpful in making predictions.

24. Correlational Study Correlation CANNOT prove causation
Do democratic parents produce better behaved children?
Do better behaved children encourage parents to be democratic?
May be an unmeasured common factor
e.g., good neighborhoods produce democratic adults and well-behaved children
Doesn’t mean they are not useful – Correlation in smoking (3 min)

28. Correlation & Causation
There is a strong +.90 correlation in shoe size and IQ.
Does this mean that a large shoe size is the cause for higher intelligence?
What else could explain this?
YOUR FEET GROW
AS YOU GET OLDER &
WISER

29. Illusory Correlation
A perception can be formed that there is a relationship between events, actions and behaviors when, in fact, no relationship exists.
Example: A football fan believes that every time he wears a specific jersey his team wins, so each time they play, he will only wear that jersey.
Need More Examples?

30. Coefficient of Correlation
Numerical indication of magnitude and direction of the relationship between two variables
Positive correlation—two variables vary systematically in the SAME direction
Negative correlation—two variables vary systematically in OPPOSITE directions

31. How to Read a Correlation

32. Positive Correlation
As the value of one variable increases (or decreases) so does the value of the other variable.
A perfect positive correlation is +1.0.
The closer the correlation is to +1.0, the stronger the relationship.

35. Negative Correlation
As the value of one variable increases, the value of the other variable decreases.
A perfect negative correlation is -1.0.
The closer the correlation is to -1.0, the stronger the relationship.

38. Zero Correlation
There is no relationship whatsoever between the two variables.

39. Let’s Review