1. Part 2: Research Methods

2. Why is psychological research important? Psychologists do more than just wonder about human behavior Psychological research has an enormous impact on all facets of our lives – how parents choose to discipline their children – how companies package and advertise their products – how governments choose to punish or rehabilitate criminals Understanding how psychologists do research is vital to understanding psychology itself.

3. Scientific Method Question/Observation Hypothesis Test Hypothesis Results Conclusions Theory Additional hypothesis Reject and revise hypothesis Other psychologist replicate and test their theories

4. Survey Method Case-Study Method Longitudinal Method Cross-Sectional Method Naturalistic Observation Method Description Advantages Disadvantage s Research Methods

5. Experimental Method Hypothesis Dependent variable Independent variable Control group Experimental group

6. Extraneous Variables in Experiments Variables other than the independent variable that could affect the dependent variable are called extraneous variables. – Example: An educational psychologist has developed a new learning strategy and is interested in examining the effectiveness of this strategy. The experimenter randomly assigns students to two groups. All of the students study text materials on a biology topic for thirty minutes. One group uses the new strategy and the other uses a strategy of their choice. Then all students complete a test over the materials.

7. Dealing With Extraneous Variables Random Assignment – participants have an equal chance of being placed in each group.

8. Advantages of Experimental Method Can show cause-and-effect relationships between variables

9. Disadvantage of Experimental Method Can not be generalized to the real world because an artificial situation. Cant be used to study everything – Cant control variables – Unethical

10. Bias in Research Bias is the distortion of results by a variable. – Sampling bias occurs when the sample studied in an experiment does not correctly represent the population the researcher wants to draw conclusions about. – Subject bias - Research subjects’ expectations can affect and change the subjects’ behavior, resulting in subject bias. Such a bias can manifest itself in two ways: Placebo effect Social desirability bias – Experimenter bias occurs when researchers’ preference or expectations influence the outcome of their research. Researchers see what they want to see. Double-blind experiment

11. Correlations Used to describe how two sets of data relate to each other – Ex: students grades and number of hours slept Correlation coefficient measures the strength of the relationship between two variables. – Always a number between –1 and +1. – The sign (+ or –) of a correlation coefficient indicates the nature of the relationship between the variables.

12. A positive correlation (+) means that the variables move in the same direction. Example: The more years of education a person receives, the higher his or her yearly income is.

13. A negative correlation (–) means that when one variable increases, the other one decreases. Example: The more hours a high school student works during the week, the fewer A’s he or she gets in class.

14. No correlation – variables do not relate

15. The higher the correlation coefficient, the stronger the correlation. – A +0.9 or a –0.9 indicates a very strong correlation – A +0.1 or a –0.1 indicates a very weak correlation. – A correlation of 0 means that no relationship exists between two variables.

17. correlation is not the same as causation. Two factors may be related without one causing the other to occur. Often, a third factor explains the correlation. – A psychologist uses the survey method to study the relationship between balding and length of marriage. He finds that length of marriage correlates with baldness. However, he can’t infer from this that being bald causes people to stay married longer. Instead, a third factor explains the correlation: both balding and long marriages are associated with old age.

18. APA Ethical Guidelines for Research In the past, researchers performed all kinds of questionable experiments in the name of science. Now psychologist must submit their research proposals to the Institutional Review Board (IRB) - Procedural errors - Ethical Violations *For humans and animals*

19. Human Research 1. Informed Consent – participants must know that they are involved in research and give their consent or permission

20. 2. Deception – if the participants are deceived in any way about the nature of the study, the deception must not be so extreme as to invalidate the informed consent. Also, researchers must be very careful about the trauma deception may cause.

21. 3. Coercion – participants cannot be coerced in any way to give consent to be in the study.

22. 4. Anonymity – the identities and actions of participants must not be revealed in any way by the researcher.

23. 5. Risk – participants cannot be placed at significant mental or physical risk. This clause requires interpretation by the review board.

24. 6. Debriefing procedures –participants must be told of the purpose of the study and provided with ways to contact the researchers about the results.

25. Milgram Experiment Milgram Experiment Original Video http://www.youtube.com/watch?v=W147ybOdgpE http://www.youtube.com/watch?v=W147ybOdgpE Milgram Experiment Video 2 http://www.youtube.com/watch?v=HwqNP9HRy7Y

26. The Holocaust https://www.facinghisto ry.org/for- educators/educator- resources/readings/rese rve-police-battalion-101 https://www.facinghisto ry.org/for- educators/educator- resources/readings/rese rve-police-battalion-101 https://www.youtube.c om/watch?v=JJ6umV7C VY8 https://www.youtube.c om/watch?v=JJ6umV7C VY8

27. Animal Research 1.Purpose- research must have a clear scientific purpose. 2.Care – animals must be cared for and housed in humane way. 3.Acquiring animals – animals must be aquired legally. 4.Suffering – experimental procedures must employ the least amount of suffering feasible. 5.Supervision – trained psychologist must supervise all animal research.

28. #1 David Reimer 1965 – 2004

29. #2 The Well of Despair 1960

30. #3 Milgram Study 1974

31. #4 Learned Helplessness 1965

32. #5 Little Albert 1920

33. #6 Landis’ Facial Expressions Experiment 1924

34. #7 Monkey Drug Trials 1969

35. #8 Stanford Prison Experiment 1971

36. #9 The Aversion Project 1970s and 1980s

37. #10 The Monster Study 1939

38. Qualitative Data Deals with descriptions Data can be observed but not measures

39. Quantitative Data Deals with numbers Data can be measured

40. – Frequency Distribution Frequency distribution table Histogram Frequency polygon Descriptive Statistics

41. LETS TRY IT! Fifteen people were asked to state the number of hours they exercise in a seven day period. The results of the survey are listed below. Make a frequency table and histogram to display the data. 8, 2, 4, 7.5, 10, 11, 5, 6, 8, 12, 11, 9, 6.5, 10.5, 13

42. Frequency Distribution Table Hours of ExerciseTallyFrequency 0 – 2I1 3 – 5I 2 6 – 8I I I I I5 9 – 11I I I I I5 12 – 14I 2

44. More Descriptive Statistics Central Tendency – Mode – Median – Mean Variance – Range – Standard deviation Correlation coefficients $25,000-Pam $25,000- Kevin $25,000- Angela $100,000- Andy $100,000- Dwight $200,000- Jim $300,000- Michael

45. Closer Look at Standard Deviation Standard Deviation: The Standard Deviation is a measure of how spread out the numbers are. The higher the variance or SD, the more spread out the distribution is. Do scientists want a big or small SD? Example: There was a, now discredited, theory proposed that claimed in IQ tests Men and Women had the same average IQs but men had a larger standard deviation than women. That is that there were more male geniuses and mentally challenged people than women. While woman's IQs tended to sit more around the average.

46. Why is Standard Deviation Important? using the Standard Deviation we have a "standard" way of knowing what is normal, and what is not.

47. How to Calculate Standard Deviation of a Sample

48. Inferential Statistics -Measures of Statistical Significance -Probability results are due to chance less than 5% to be statistically significant

49. Lets Try It! Suppose we want to test the effectiveness of a medicine to reduce the likelihood of a heart attack. We design a controlled study of two groups of people. Group A takes the medicine, and Group B takes a placebo. Suppose that Group A has a much lower rate of heart attacks than Group B. Is this due to chance, or the medicine? – Suppose the p-value for the study is.04. – Suppose the p-value had been.1.