1. RESEARCH METHODS

2. Goals of Psychology Describe Explain Predict Control
…………behavior and mental processes

3. Critical Thinking
Thinking that does not blindly accept arguments or conclusions but questions their validity
NOT parsimonious thinking (willingly accepting the most simple explanation).

4. Scientific Method
Technique using tools such as observation, experimentation, and statistical analysis to learn about the world
Through its use, psychology is thereby considered a science.

5. Steps to the Scientific Method
Form a testable question
Develop a hypothesis
Test Hypothesis - Design study to collect data
Experimental
Descriptive
Analyze data
Use of statistical procedures
Use of meta-analysis
Draw a conclusion
Report results
Publication
Replication

6. Things That Make Us WRONG: Why we need the scientific method

7. Common Sense
Conclusions based solely on personal experience and sensible logic
Most of the time it is good but…
Can lead to incorrect conclusions

8. What are the Odds of Each?

9. What are the Odds of Each?
1 in 2,598,960

10. What are the Odds of Each?
1 in 2,598,960
1 in 2,598,960

11. Did you know…
It is nearly impossible to fold a regular sheet of paper in half more than 7 times.
Go ahead and try!
Mythbusters pulled it off with a piece of paper as big as an airplane hanger and a steam roller.

12. Science vs. Common Sense
Science helps build explanations that are consistent and predictive as opposed to conflicting and describing the past (hindsight)
Science is based on
knowledge of facts
developing theories
testing hypotheses
public and repeatable procedures

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

14. Hindsight Bias
The tendency to exaggerate one’s ability to have foreseen how something would turn out after learning the outcome.
The “I knew it all along” phenomenon.
Week before the 1985 Super Bowl, 81% of Dr. Brigham’s students predicted the Miami Dolphins would win. 40% said the Dolphins would win by 10 or more points.
A week after San Francisco 49ers decisive victory, he asked the group who picked the 49ers.
58% said they picked the 49ers
NO ONE remembered saying the Dolphins would win by at least 10 points.

15. Overconfidence
Tendency to overestimate the accuracy of our current knowledge
We are more confident than we are correct.
How many of you overestimated the number of correct answers on your True/False Quiz?

16. Confirmation Bias
Our tendency to search for information that confirms our beliefs and ignore those that don’t.
Try this card trick:
This works because we only look for our chosen card confirming Simeon’s mental telepathy and ignore the fact that second set of cards is in fact, an entirely new set!
NONE of the cards in the new set is the same as the old one so of course the card you picked is missing.

17. Researcher Bias
The tendency to notice evidence which supports one particular point of view or hypothesis

18. Volunteer Bias
People who volunteer to participate in a survey differ from those who do not.
Those who complete it are often willing to share, have similar interests, have spare time (magazine surveys).
These factors skew or slant the results.
Eliminate this by using a random sample where everyone has equal chance of being chosen to participate.

19. Participant Bias
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

20. Eliminating Bias
“Placebo Effect” – participants react because they THINK they are receiving treatment (sugar pill)
Mind over Matter
“Nocebo” – If told a drug won’t work, the person will feel it doesn’t work even if it is a legitimate drug.
Single Blind Study – participants do not know if they are getting the treatment or not
Double Blind Study – neither the researcher or the participants know if they are getting the treatment or not

21. Research Strategies Fall Into 2 Categories
Descriptive—strategies for observing and describing behavior
Observation
Surveys
Experimental—strategies for inferring cause and effect relationships among variables

22. Longitudinal Study
Researchers study the same group of individuals for many years to see how they change.
Can be very expensive and difficult to conduct
Risky – people may drop out
Ex: Ruby Payne studied poverty

23. Cross-Sectional Study
Researchers simultaneously study a number of subjects from different age groups and then compare the results to see how they are different.
Cheaper, easier than longitudinal studies, but group differences may be due to factors other than development. (More variables.)

24. Longitudinal/Cross Sectional Study

25. Naturalistic Observation
Method of observation where subjects are observed in their “natural” environment
Subjects are not aware they are being watched – researcher does not interfere
Could use hidden cameras or two way mirrors
Ex: People eating in a restaurant

26. Laboratory Observation
Not always a sterile room.
Place where the environment can be controlled to minimize the number of variables.
Negatives are that it may cause the subject to act differently than it normally would.
Ex: Skinner Box, maze, fish tank

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

28. Survey Method
Research method that relies on self-reports; uses surveys, questionnaires, interviews.
Usually a very efficient and inexpensive method; able to get a large sample
Can you guess some limitations of this method of research?

29. Survey Limitations
Accuracy is a concern; people are not always honest.
They fear confidentiality or want to please the researcher.
Example: Tooth brushing survey in 1960s. If as many people actually brushed their teeth as often as they claimed to brush their teeth, 33% (?) more toothpaste would have been sold that year.

30. Sampling Terms
(Target) Population—large (potentially infinite) group represented by the sample. Findings are generalized to this group.
Sample—selected segment of the population for the study
Stratified or Representative sample—closely parallels the target population on relevant characteristics; sample is proportional to TARGET POPULATION
Random selection—every member of larger group has equal chance of being selected for the study sample

31. Random Sample A sample that represents the target population:
Each member of the population has an equal chance of being included.
If a sample is not random it is said to be biased.
Increase chances of representing population when sample is BIG ENOUGH
How would you pick a random sample???

32. Generalizing the Results
Applying the findings from the research group to other groups.
Be cautious about generalizing when it isn’t a random or stratified sample.
Example: Car preference differs between men, women, region, socio-economic background, and more.

33. Correlational Study
Correlations examine relationships between categories of facts.
Correlation reveals relationships among facts
e.g., more democratic parents have children who behave better
A correlational study does NOT determine HOW the two variables are related – just that they are related
Correlational studies are helpful in making predictions.

34. 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
Does NOT determine why the two variables are related--just that they are related.

35. 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

36. 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.

38. 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.

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

41. The Only Way to Show Cause & Effect
Experimental Design
The Only Way to Show
Cause & Effect

42. Experimental Terms Variable – part of experiment that changes
Independent Variable (IV)– controlled by researcher. This variable causes something to happen.
Dependent Variable (DV) – watched by the researcher to see the impact of the IV. This variable is the effect that is caused by the IV.
Good Way to Remember the difference: An IV in your arm causes something to happen (DV)
Confounding Variable – things that cannot be controlled that can influence the experiment

43. Groups Experimental group – receives the treatment; frequently a drug
Control group – receives no treatment; usually receives a placebo (fake drug)

44. Limitations of Experiments
Conditions in an experiment may not reflect conditions of real life.
(Must simplify variables to get useful information.)
Ethical considerations in creating some more “real life” situations

45. Research Ethics
Confidentiality – participants are more likely to be truthful if they know their privacy is protected.
Confidentiality can be broken if information reveals harm to another person

46. Ethics
Informed consent – some studies may have long term threats or irreversible effects.
Participants must be given a choice to participate after being informed of the study.
Deception is allowable when benefit outweighs harm and participants receive full explanation at its conclusion

47. Animal Research APA has rules for animals, too.
Often used instead of humans when topic could not be ethically studied on a human.
Ex: Early separation studied by Harlow in 1959 with monkeys.
Animal experiments lead to solutions with humans – eating disorders, drug treatments
Still controversial due to the fact that animals can be harmed in studies.