1. How do you know what you know? How do you know it? What don’t you know? Why don’t you know it?

2.  The scientific revolution and the subsequent discoveries made us smarter!  So, how does that research work for Psychology…what are the different methodologies?  Here is an example of Psychological research…Psychological research…

3.  There are various Methodologies? methodology - According to the text, methodology simply refers to the methods that we use to conduct an investigation. describe behaviorexplain its causespredict behaviors may occur again control certain behaviors The goals of research are to describe behavior, to explain its causes, to predict the circumstances under which certain behaviors may occur again, and to control certain behaviors. Psychologists use various methods of research to accomplish each of these goals. As we go through this, try to figure out what kind of research you would like to do…  Milgrim Short Version Milgrim Short Version  Milgrim Full Version Milgrim Full Version

4. Naturalistic Observation: Naturalistic Observation: A research method in which the psychologist observes the subject in a natural setting without interfering. (In other words…Watch, but do not touch!)

5.  Participant Observation:  Participant Observation: A research method in which the psychologist observes the subject in a natural setting but gets involved. (In other words…Watch AND interact

6. Surveys: Surveys: A research method in which information is obtained by asking many individuals a fixed set of questions. This is usually used to get an idea of the population’s attitudes toward something. Note: - Note: These are only accurate if they are representative of the population as a whole.

7.  Longitudinal Study:  Longitudinal Study: A research method in which data is collected about a group of participants over a number of years to assess how certain change or remain the same during development. Cross Sectional Studies: Cross Sectional Studies: A research method in which data is collected from groups of participants of different ages and compared so that conclusions can be drawn about differences due to age.  Experiments  Experiments : A research method in which variables are manipulated in order to determine causation. While surveys and other methods are good at determining Correlation…experiments are good at determining Causation

8. Case Studies: Case Studies: A research method that involves an intensive investigation of one or more participants. (long term, very involved.) Note: - Note: By itself, a case study does not prove or disprove anything. The researchers conclusions may not be correct. This was the technique used by Freud.

9.  Case studies may be used to describe particularly rare phenomena. The study of presidential assassins is limited to case studies of a few people who have killed or tried to kill U.S. Presidents. Investigations of mass murderers are also limited to case studies.

10. Study things that are difficult to test. -ethically, there are limits to what we can study…or is there?  Video 4 of 5 2:00-7:00 Video 4 of 5 2:00-7:00

11.  Case studies provide illustrative anecdotes. Researchers and teachers often use case studies to illustrate general principles to students.

12.  There are also at least 2 major limitations to case studies: 1.) They are virtually useless in providing evidence to test behavioral theories or treatments.  The lives and events studied often occur in an uncontrolled fashion and without comparison information.  No matter how reasonable a researchers explanations may be, you cannot rule out alternative explanations.

13. 2.) Most case studies rely on the observations of a single investigator.  We often have no way of assessing the reliability of that single researcher’s observations and interpretations.  Because the researcher may have some sort of vested interest in the outcome of the study, one must always be concerned about the self-fulfilling prophecy.

14. 2. Surveys

15.  Surveys are very appealing. Seems like an efficient way to do research.  What are some of the flaws that you can think of with surveys? Wording Audience Order Who is asking?

16.  Wording: How can the wording of a survey influence the responses given?  “ Sex” vs. “Relations”  “Hate” vs. “Dislike”  “Love” vs. “Like”

17.  Audience: How can the audience to which the survey is given influence the responses?  Location and topic  How are the questions asked?

18.  Order: How can the order in which the questions are asked influence the responses? -1.) Do you think the actions of the Sept. 11 th attacks were wrong? -2.) Does is anger you that American soldiers are dying in Iraq? -3.) Do you think people in the Middle East are generally violent?

19.  Who is asking? How could the person asking influence the answers given?  Race  Gender  Background  Inflection

20.  Why is it important to have random samples in survey research? Some fun statistics:  68% of people roll toilet paper over the spool  79% squeeze toothpaste from the top  7% look behind the shower curtain when using someone else’s bathroom  80% of people eat corn on the cob in circles instead of rows  10% of people have seen a ghost  7% of people have flossed their teeth with their own hair

21.  What was wrong with each one of those statistics? Those responses were the results of only about 7,000 people out of 25,000 surveyed.

22.  Obtaining random samples for any purpose is difficult. The government has had no more success than the private sector. The 1970 lottery to determine the order of the military draft was almost certainly unfair. The 31 capsules for January were placed in the bin first, then the 29 for February, and so on until the 31 for the next December. What do you think happened when the bin was not turned enough?  The December Birthdays were drawn much earlier.

23.  You need to be aware of the difference between correlation and causation

24.  Correlation:  Correlation: The measure of a relationship between two variables or sets of data.  Whaaaaaaaaaaaaaa?  There are 2 types of Correlation. Positive and Negative. positive correlation  For example, there is a positive correlation between IQ scores and academic success. Low IQ scores tend to go with low grades. negative correlation (High score = Low score, Low score = High score)  Another example, there is a negative correlation between the number of times you go down a slide and the number of times you get hurt from it. In other words, the more you practice, the less you will get hurt! (High score = Low score, Low score = High score) Why?  It is important to remember that while the word correlation describes the relationship between 2 things, it does not always mean that one thing causes the other. Why?  RELATIONSHIP….Not cause!  It is very easy to misinterpret correlation studies as a cause an effect issue, but this is not accurate.

25. A Story; In the early twentieth century, thousands of Americans in the South died from Pellagra, a disease marked by dizziness, lethargy, running sores, and vomiting.

26. Finding that families struck with the disease often had poor plumbing and sewage, many physicians concluded that pellagra was transmitted by poor sanitary conditions. In contrast, Surgeon General Joseph Goldberger thought that the illness was caused by an inadequate diet.

27. He felt that the correlation between sewage conditions and pellagra did not reflect a casual relationship, but that the correlation arose because the economically disadvantaged were likely to have poor diets, as well as poor plumbing. So, how was the controversy resolved?

28. Well, the answer demonstrates the importance of the scientific method. To prove he was right, Goldberger not only had himself injected with the blood of a victim with sores all over his body, he found a victim with diarrhea and….ate his excrement! He did NOT come down with pellagra!

29. To further make his case, Goldberger asked two groups from a Mississippi state prison farm to volunteer for an experiment. One group was given a high carbohydrate, low protein diet that Goldberger suspected to be the culprit, while the other received a balanced diet. Within months, the first group was ravaged by pellagra, while the second showed no signs of the disease.

30.  Causation refers to 1 variable causing another variable to behave a certain way.

31.  While surveys can highlight correlations, experiments can show causations  In experiments there are multiple variables Independent variable- variable that causes something to happen to DV Dependent variable- variable that shows the effect of changing the IV Confounding variable -variable other than IV that can produce a change in DV  Experimental group- participants are exposed to treatment  Control group- participants are NOT exposed to treatment  Double-Blind procedure- when the researchers and participants don’t know the procedure being used.

32.  Now, try to go back to Milgram’s Obedience experiment and figure out the following: Independent Variable Dependent Variable Experimental Group Control

33.  In order for experiments to be considered valid, they must be repeatable.  How do we really know if something is legit if it is not repeatable? Could be a one-time fluke.

34.  There are different types of bias: Confirmation bias  A tendency to search for information that confirms a pre- conception.  THIS IS DANGEROUS!!!!  WE ALL DO IT  Check out these videos…123123

35.  Now try this activity…2, 4, 6…can you figure out the rule? Write 3 numbers down that match the rule and I will tell you if it is correct or not. Then write down the rule and check it with me. Participant Bias  Research participants behave in a certain way because they know they are being observed or part of an experiment.

37.  MEAN: The MEAN is the arithmetic average, the average you are probably used to finding for a set of numbers - add up the numbers and divide by how many there are: (80 + 90 + 90 + 100 + 85 + 90) / 6 = 89 1/6.

38.  MEDIAN: The MEDIAN is the number in the middle. In order to find the median, you have to put the values in order from lowest to highest, then find the number that is exactly in the middle:  80 85 90 90 90 100 ^ since there is an even number of values, the MEDIAN is between these two, or it is 90. Notice that there is exactly the same number of values ABOVE the median as BELOW it!

39.  MODE: The MODE is the value that occurs most often. In this case, since there are 3 90's, the mode is 90. A set of data can have more than one mode.  80 85 90 90 90 100

40.  RANGE: The RANGE is the difference between the lowest and highest values. In this case 100 - 80 = 20, so the range is 20.  The range tells you something about how spread out the data are. Data with large ranges tend to be more spread out.