1. Research Methods It is actually way more exciting than it sounds!!!!

2. Why do we have to learn this stuff? Psychology is first and foremost a science. Thus it is based in research. Be aware however of two hurdles that tend to skew our logic when we research

3. Hindsight Bias The tendency to believe, after learning the outcome, that you knew it all along. Monday Morning Quarterbacking!!! Example: After Lebron made his decision to go to Miami, you say it was obvious he was going there—That’s where Wade went

4. Overconfidence We tend to think we know more than we do. 82% of U.S. drivers consider themselves to be in the top 30% of their group in terms of safety. 81% of new business owners felt they had an excellent chance of their businesses succeeding. When asked about the success of their peers, the answer was only 39%. (Now that's overconfidence!!!)

5. Overconfidence “ There is no reason for anyone to have a computerin their home.” (Ken Olson, president of Digital Equipment Company, 1977) “Heavier-than-air flying machines are impossible.”(Lord Kelvin, British mathematician, physicist, and president of the British Royal Society, 1895) “Reagan doesn’t have the presidential look.”(United Artists executive when asked whether Ronald Reagan should be offered the starring role in the movie The Best Man, 1964) “A severe depression like that of 1920–1921 is outside the range of probability.” (Harvard Economic Society, Weekly Letter, November 16, 1929) “Man will never reach the Moon, regardless of all future scientific advances.” (Lee DeForest, inventor of the vacuum tube, 1957)

6. The Scientific Attitude Three main components – Curious eagerness – Skeptically scrutinize competing ideas – Open-minded humility before nature

7. Critical Thinking Critical Thinking - thinking that does not blindly accept arguments and conclusions – “Smart thinking” – Four elements Examines assumptions Discerns hidden values Evaluates evidence Assesses conclusions – Empirical Approach

8. Scientific Method 1.Observe some aspect of the universe. 2.Invent a theory (an explanation) that is consistent with what you have observed. 3.Use the theory to make predictions, a hypothesis is a testable prediction 4.Test those predictions by experiments or further observations. 5.Modify the theory in the light of your results. 6.Go to step 3.

9. Thinking that she had outperformed most of her classmates, Glenda was surprised to receive just an average grade on her psychology test. Glenda's experience best illustrates 1.The hindsight bias 2.The placebo effect 3.Negative correlation 4.Illusory correlation 5.Overconfidence 1234567891011121314151617181920 21222324252627282930

10. According to Emily's grandfather, Adolf Hitler's obvious emotional instability made it clear from the beginning days of his international conflicts that Germany would inevitably lose World War II. The grandfather's claim best illustrates 1.the hindsight bias. 2.illusory correlation. 3.overconfidence. 4.an illusion of control 5.random sampling. 1234567891011121314151617181920 21222324252627282930

11. 3Types of Research Descriptive To describe behavior Correlational To predict behavior Experimental To explain behavior

12. 3 Types of Descriptive Research The Case Study The Survey Naturalistic Observation

13. Case Studies A detailed picture of one or a few subjects. – Sources of Info Direct Observation Interviews Documents Provide unique oppty to study unusual cases Offers suggestions for further study Results can’t be generalized Can’t establish cause and effect Example: The ideal case study was John and Kate. Really interesting, but are they typical of all

14. Naturalistic Observation Watch subjects in their natural environment. Do not manipulate the environment. May be done when it is not ethical to manipulate variables Does not show cause and effect. Example: Jane Goodall’s research on chimpanzees

15. Survey Method Method for understanding the self reported beliefs of a certain group personal facts, attitudes, past behaviors and opinions. Questionnaire or Structured interview Works with large groups of data Can be Descriptive or Correlational Cheap and fast, most used research method in psychology Example: U.S. Census

16. Conducting a Survey Population - all the possible subjects in a group you want to study Example: men and women 18-80 Random Sampling – a portion of the population that fairly represents the population because each person has an equal chance of getting chosen Ensures that the participants are representative of a large population Helps avoid false generalizations Example: Use of a random computer generator to select 1000 people in the phone book for a survey to be sent to.

17. Survey Method: The Bad Low Response Rate Response Bias - People Lie or just misinterpret themselves. Wording Effects How accurate would a survey be about the frequency of diarrhea?

18. Correlational Method Correlation - expresses a relationship between two variables. – Measures how well one variable predicts the other Can be efficient Can make predictions Can use pre-existing or archival data Make it difficult to assess the impact of a third variable Does not show causation As more ice cream is eaten, more people are murdered. Does ice cream cause murder, or murder cause people to eat ice cream?

20. Types of Correlation Positive Correlation The variables go in the SAME direction. Negative Correlation The variables go in opposite directions. Example: Studying and grades hopefully has a positive correlation. Example: Heroin use and grades probably has a negative correlation.

21. Correlation Coefficient A number that measures the relationship between 2 variables. Range is from -1 to +1 – The relationship gets weaker the closer you get to zero. Scatterplot – a visual representation of the relationship between the variables – shown as a graphed cluster of dots Which is a stronger correlation? -.13 or +.38 -.72 or +.59 -.91 or +.04

22. Which of the following would be a negative correlation, and which would be a positive correlation? Education and years in jail Weight and hours of TV watched Education and income Holding babies and crying Food and calories ingested

23. Correlation

26. The table below lists the scores of eight research participants on a test to measure anxiety, as well as the typical number of cigarettes each person smokes daily. Scores on the anxiety test can range anywhere from a low of 0 (indicating very low anxiety) to a high of 30 (indicating very high anxiety). Research Anxiety Cigarettes Participant Test Score____________ 1 8 11 2 9 3 3 15 11 4 14 16 5 21 26 6 12 10 7 22 24 8 17 18 Construct a scatterplot to represent the correlation between smoking and anxiety. Describe the direction of the correlation and give two possible explanations for it.

27. Correlation Illusory Correlations Illusory Correlation – Perceived non-existent correlation – A random coincidence

28. Speaking at a college graduation ceremony, Professor Robson compared college graduates with adults who are less educated. She correctly noted that college graduates pay more taxes, vote more frequently, engage in more volunteer activities in their communities, and are less likely to go to jail than less-educated adults. The professor concluded that colleges obviously do great things for society. How might you reasonably challenge the way the professor reached her conclusion?

29. Psychologists who carefully watch the behavior of chimpanzee societies in the jungle are using a research method known as 1.The survey 2.Experimentation 3.Naturalistic observation 4.The case study 5.Random sampling

30. If psychologists discovered that wealthy people are less satisfied with their marriages than poor people are, this would indicate that wealth and marital satisfaction are 1.Causally related 2.Negatively correlated 3.Independent variables 4.Dependent variables 5.Positively correlated

31. The belief that weather conditions signal the onset of arthritis pain best illustrates 1.Random sampling 2.The hindsight bias 3.The placebo effect 4.An illusory correlation 5.overconfidence

32. Which of the following correlation coefficients expresses the strongest degree of relationship between two variables? 1.+0.10 2.-.67 3.0.00 4.-0.10 5.+0.59

33. Experimental Method Manipulation of one or more variables Shows cause and effect Have high internal validity – confidence that IV influences DV Replication allows for verification of results Can eliminate bias through double-blind procedures Confounding variables Time and $ Smoking causes health issues.

34. Theory An explanation that organizes observation and predicts behaviors or events A hunch Example: – Participating in class leads to better AP scores

35. Hypothesis A testable prediction. Example: Students who participate in AP Psych class will score higher on the AP exam

36. Operational Definitions A statement that tells a person clearly Meaning of hypothesis how to perform an observation measure a variable Must be clear and precise Must be measurable Allow experiment to be replicated Example: Participation is the number of times a person raises their hand in class to answer or ask a question about AP Psych content

37. Independent Variable Whatever is being manipulated in the experiment. If there is a drug in an experiment, the drug is almost always the independent variable. Example: Participation

38. Dependent Variable The dependent variable would be the effect of the drug. Whatever is being measured in the experiment. It is dependent on the independent variable. Example: Score on the AP Exam

39. Beware of Confounding Variables Examples: A factor other than the independent variable that might produce an effect on the experiment Confounds often arise due to differences between the groups that exist before the independent variable is imposed! motivation, eagerness to please, lifestyle, age, intelligence…. * Other confounding variables in an experiment could be experimenter bias or the placebo effect but we’ll talk about those later…

40. Assignment Random Assignment – Assigning participants in an experiment to experimental and control groups by chance – Minimizes differences between two groups – Different than Random Sample – Reduces the impact of confounding variables Experimental Group – the group that’s exposed to the treatment Control Group – the group not exposed to the treatment Examples: Experimental - The group that gets to participate Control group – The group that does not get to participate

41. 2 other confounding variables Experimenter Bias - expectations by the experimenter that are subtly communicated to the participants Placebo effect – an experimental effect caused by expectations of participants or caused by a substance which the recipient assumes is the independent variable but is not (ie. A drug that has no effect is assumed to be the drug that has an effect).

42. Double-blind Procedure Both the researcher and the participants are ignorant about who is receiving the treatment and who is receiving a placebo ( a dummy medication) Minimizes placebo effect and experimenter bias

43. Replication Repeating the research study to see whether the basic finding extends to other participants and circumstances. What helps the researcher to insure the study can be replicated?

44. Researchers use experiments rather than other research methods in order to distinguish between 1.Facts and theories 2.Cause and effects 3.Case studies and surveys 4.Random samples and representative samples 5.Hypotheses and operational definitions 1234567891011121314151617181920 21222324252627282930

45. Abdul has volunteered to participate in an experiment evaluating the effectiveness of aspirin. Neither he nor the experimenters know whether the pills he takes during the experiment contain aspirin or are merely placebos. The investigators are apparently making use of 1.Naturalistic observation 2.Illusory correlation 3.The double-blind procedure 4.Random sampling 5.The overconfidence effect 1234567891011121314151617181920 21222324252627282930

46. In the hypothesis “Students who study a list of terms in the morning, just after waking up, will recall more terms than students who study the list just before falling asleep,” what is the dependent variable? 1.List of terms 2.Memorization 3.Time of day 4.Number of terms remembered 5.students 1234567891011121314151617181920 21222324252627282930

47. In a study conducted on depression, some patients were given an anti-depressant and others were given a placebo to test whether the drug reduced suicidal thoughts. What is the independent variable in this study? 1.Anti-depressant 2.Placebo 3.Number of suicidal thoughts 4.Depression 5.Patients 1234567891011121314151617181920 21222324252627282930

48. Statistics Recording the results from our studies. Must use a common language so we all know what we are talking about.

49. Descriptive Statistics Just describes sets of data. You might create a frequency distribution. Examples: Frequency polygons, bargraphs or histograms.

50. Types of Data Nominal Data – identifies categories Ordinal Data – identifies the order in which data falls in a set Interval data – data that falls within a number line with a zero starting point Ratio data – data that falls in a number line where zero is just another number Examples: Yes/No answers, class level in school (Sr., Junior etc.) Any Ranking of items – class rank, music hits Weight and Height Temperature

51. Measures of Central Tendency Mode (occurs the most) Mode Mean (arithmetic average) Mean Median (middle score) Median

52. Central Tendency Mean, Median and Mode. $25,000-Pam $25,000- Kevin $25,000- Angela $100,000- Andy $100,000- Dwight $200,000- Jim $300,000- Michael Let’s look at the salaries of the employees at Dunder Mifflen Paper in Scranton: The median salary looks good at $_______________________ The mean salary also looks good at about $________________ But the mode salary is only $___________________________ 100,000 110,000 25,000 Watch out for extreme scores or outliers. Medium is a better measure than the mean when there are extremes

53. Normal Distribution In a normal distribution, the mean, median and mode are all the same. Examples: Height, Weight, IQ Scores

54. Distributions Outliers skew distributions. If group has one high score, the curve has a positive skew (contains more low scores) If a group has a low outlier, the curve has a negative skew (contains more high scores) If most students scored well on a test, what would the distribution look like? If most students scored poorly? What does the data tell us?

55. Measures of variability Range: distance from highest to lowest scores. Standard Deviation: the variance of scores around the mean. The higher the variance or SD, the more spread out the distribution is. Do scientists want a big or small SD? Variance - The average of the squared differences from the mean – another measure of how the data is distributed around the mean Shaq and Kobe may both score 30 ppg (same mean). But their SDs are very different…meaning?

56. Calculating Standard Deviation Step 1 – calculate the mean – add all of the raw scores and divide by the # of scores Step 2 – calculate the deviation from the mean by subtracting each of the raw scores from the mean Step 3 – square the deviation from the mean for each score Step 4 – Sum the squared deviations Step 5 – divide the sum of the squared deviation by the number of scores and find the square root

57. Calculating the Standard Deviation

58. Calculating the Standard Deviation your turn Scores – 10, 3, 7, 8, 7 Step 1 – calculate the mean – add the all of the raw scores and divide by the # of scores Step 2 – calculate the deviation from the mean by subtracting each of the raw scores from the mean Step 3 – square the deviation from the mean for each score Step 4 – Sum the squared deviations Step 5 – divide the sum of the squared deviation by the number of scores and find the square root 35/5 = 7 10-7 = +3, 3-7 = -4, 7-7 =0, 8-7= +1, 7-7=0 3x3=9, 4x4=16, 0x0=0, 1x1=1, 0x0=0 9+16+0+1+0 = 26 26/5 = 2.28

59. Variance The average of the squared differences from the Mean. = Standard Deviation 2 Example: Standard Deviation = 5 Variance = 25 *if you know the variance, how can you calculate the standard deviation?

60. Scores A unit that measures the distance of a score from the mean in units of standard deviations Observation – Mean Standard Deviation 10-15 = -1 5 Equals 0 at the mean A positive z score = number above the mean, negative z score = number below the mean. Example: If John scored a 72 on a test with a mean of 80 and a standard deviation of 8, John’s z score would be

61. Normal Distribution What is the probability an observation is less than the z score or more than the z score?

62. Normal Distribution Calculating the % of the observed Step 1 – calculate the mean Step 2 - calculate/find the standard deviation or variance. If you only have the variance you must calculate the standard deviation Step 3 draw a normal distribution curve and find the scores for each standard deviation from the mean and place them on the graph Step 4: calculating the % of students who scored within a range of scores by finding the corresponding scores on the curve, then add the percentages from each standard deviation.

63. Inferential Statistics The purpose is to discover whether the finding can be applied to the larger population from which the sample was collected. Statistical Significance – the observed difference between the means of the experimental and control group are not due to chance Measured by P-value=.05 – 5% likely the results are due to chance or – 95% confidence level the results are due to the independent variable – You can apply the findings to the population What does a p-value=.80 mean? that you are only 20% confident the difference in means is due to the independent variable

64. Statistical Significance Key Ideas The bigger the difference between groups the less likely it is that it's due to chance. The larger the sample size (number of patients) the more likely it is that the observed difference is close to the actual difference. This is an example of the "law of large numbers." – Ie. The smaller the real difference is, the more patients you need to be likely to detect a statistically significant difference in a clinical trial. The larger the real difference is, the fewer patients you need to be likely to be detect a statistically significant difference in an actual clinical trial. The larger the sample size, the smaller an observed difference has to be in order to be statistically significant. The smaller the sample size, the larger an observed difference would have to be in order to be statistically significant.

65. APA Ethical Guidelines for Research IRB- Internal Review Board Both for humans and animals.

66. Animal Research Clear purpose Treated in a humane way Acquire animals legally Least amount of suffering possible.

67. Human Research Informed consent Confidentiality No harm Must debrief

68. Milgram’s Experiment “teachers” were ordered to shock “learners” for wrong answers Criticized for deceiving “teachers” and subjecting them to stress 65% of participants followed the orders to the maximum shock level

69. Milgram’s Experiment Obedience High – Experimenter in close proximity to “teacher” – Learner placed in a different room – Experiment associated with prestigious location (Yale) Obedience Lower – Experimenter out of the room giving orders over a phone – Other “teachers” observed other participants refuse orders – Experiment not associated with prestigious location