1. Chapter 2: The Research Enterprise in Psychology Part 1 AP Psychology 2014-2015

2. The Scientific Approach: A Search for Laws Basic assumption: events are governed by some lawful order Goals: 1.Measurement and description 2.Understanding and prediction 3.Application and control

3. Figure 2.1 Theory construction

4. Figure 2.2 Flowchart of steps in a scientific investigation

5. The Scientific Method: Terminology Operational definitions are used to clarify precisely what is meant by each variable Participants or subjects are the organisms whose behavior is systematically observed in a study Data collection techniques allow for empirical observation and measurement Statistics are used to analyze data and decide whether hypotheses were supported

6. Table 2.1 Key Data Collection Techniques in Psychology

7. The Scientific Method: Terminology Findings are shared through reports at scientific meetings and in scientific journals – periodicals that publish technical and scholarly material ▫Advantages of the scientific method: Clarity of communication and relative intolerance of error Research methods: General strategies for conducting scientific studies

8. Peer Review of Scientific Articles The process of publishing scientific studies allows other experts to evaluate and critique new research findings. They carefully evaluate each study’s methods, statistical analyses, and conclusions, as well as its contribution to knowledge and theory. The purpose of the peer review process is to ensure that journals publish reliable findings based on high- quality research.

9. Figure 2.4 The peer review process for journal submissions.

10. Experimental Research: Looking for Causes Experiment = manipulation of one variable under controlled conditions so that resulting changes in another variable can be observed ▫Detection of cause-and-effect relationships Independent variable (IV) = variable manipulated Dependent variable (DV) = variable affected by manipulation ▫How does X affect Y? ▫X = Independent Variable, and Y = Dependent Variable

11. Operational Definition Used to quantify and clarify what is meant by each variable Used to be able to measure IV and DV Example: Studying helps students succeed in school. ▫Independent Variable—studying ▫Dependent Variable—success in school ▫How do we measure or test what the IV and DV are?  Operational Def of IV: # of hours  Operational Def of DV: grade on test

12. Experimental and Control Groups: The Logic of the Scientific Method Experimental group Control group ▫Random assignment ▫Manipulate independent variable for one group only ▫Resulting differences in the two groups must be due to the independent variable Extraneous and confounding variables Placebo effect Video: Strange Powers of the Placebo Effect

13. Extraneous/Confounding Variables Extraneous: Any variables other than the independent variable that seem likely to influence the dependent variable Confounding: When two variables are linked together in a way that makes it difficult to sort out their independent effects Confounding variables are TYPES of extraneous variables

14. Extraneous Variables Variables that affect the DV and are linked to the IV. When extraneous variables are recognized during the design stage of the experiment, researchers use techniques to turn them into controlled variables. If extraneous variables go unrecognized, they become confounded variables.

15. Confounded experiments If an experiment has a third variable that changes as the IV changes, the logic of the experiment is compromised. Any change in the DV that accompanies a change in the IV might be due to this third variable rather than the IV. If a third variable in an experiment is linked with the IV, the experiment is said to be confounded. Confounded variables are unfortunate. Although saying that they ruin an experiment is too strong, confounded variables do keep interpretations from being straightforward statements about the relationship between the IV and the DV. When a confounded variable could have been removed from an experiment but was not, the expression, CONFOUND IT! is appropriate.

16. For example… To study the effects of medication to treat depression while also undergoing counseling…. You randomly assign people diagnosed as depressed into control and experimental groups. The control group is given placebo pills by Nurse A and talks to Counselor A for one hour every week. The experimental group is given your test pills by Nurse A but sees Counselor B for one hour every week. You find that the experimental group feels better at the end of the study. Unfortunately, you're study is not valid because the two groups saw different counselors. We can't say that it wasn't the counselor that made the subjects better, so your study is confounded. The differing techniques of the counselors are extraneous variables.

17. Controlled Variables When a potentially confounded variable is controlled, the logic of an experiment remains intact.

18. Nuisance Variables Another type of extraneous variable… Characteristics of the participants or the situation that makes the effects of the IV difficult to see Noise, uncomfortable temperatures, differences in IQ,

19. Terms Definition Dependent variable (DV)The behavior or outcome that is measured. It is expected to change as a result of changes in the IV Independent variable (IV)Variable with two or more levels chosen by the researcher. Changes in the IV are expected to be related to changes in the DV. Confounded variableVariable that changes concurrently with the IV. The DV is affected by both the IV and the confounded variable. Controlled variableVariable that changes concurrently with the IV, but whose effects can be distinguished from those of the IV. Extraneous variableGeneral term for a variable that changes concurrently with the IV. Nuisance variableVariable that causes DV scores to be more variable

20. Experimental Designs: Variations Expose a single group to two different conditions ▫Reduces extraneous variables ▫When subjects serve as their own control group, the experiment is said to use a within-subjects design ▫When two or more independent groups of subjects are exposed to a manipulation of an independent variable, the experiment is said to use a between-subjects design

21. Experiment Question Will Johnny get more phone numbers from girls if he wears Axe Body Spray? Independent Variable Axe Body Spray Operational Definition of the Independent Variable Before approaching the girls, Johnny will spray the Harmony scented Axe body spray evenly across his body for three seconds. Dependent Variable The quantity of phone numbers Johnny acquires Operational Definition of the Dependent Variable The number of phone numbers, Twitter addresses, email addresses, or Kik usernames that Johnny acquires. Control Condition (Group) Johnny wearing NO Axe body spray Experimental Condition (Group) Johnny wearing Axe body spray Potential Extraneous Variables Johnny’s personality, physical appearance, body odor, intelligence; The personal preferences of the girls he talks to How we will prevent confounding variables Johnny will be given a standard dialogue to use & outfit to wear. The girls will be pre-screened. Experiment Summary Johnny will ask 10 girls for their phone numbers while wearing no Axe body spray. Then, he will ask 10 other girls for their phone numbers while wearing Axe body spray.

22. Experimental Designs: Variations Manipulate more than one independent variable ▫Allows for study of interactions between variables ▫Ex: study the effects of having the radio on when people work on an assembly line…you’d collect data from the same group of workers twice, once with the radio on and once with it off. Use more than one dependent variable ▫Obtains a more complete picture of effect of the independent variable ▫Ex: measure not only number of pieces workers finish when the radio is allowed to be on while they work, but also worker satisfaction, absenteeism, and attitude.

23. Figure 2.6 The basic elements of an experiment

24. Population vs. Sample Population: everyone of interest to whom a study can be applied Sample: a portion of the population that is part of the study Random sample: each item or member of the population has an equal chance of being selected Representative sample: A small group whose characteristics accurately reflect those of the larger population from which it is drawn

25. Advantages and Disadvantages of Experimental Research Strengths: ▫conclusions about cause-and-effect can be drawn Weaknesses: ▫artificial nature of experiments ▫ethical and practical issues

26. Biases Hindsight Bias: “I knew it all along” phenomenon After learning the outcome of an event, many people believe they could have predicted that very outcome. Ex: 9/11 Ex: dot.com stocks plummeting

27. Confirmation Bias Searching for or interpreting new information in a way that confirms your beliefs Ex: A teacher looking for ways that girls have scored better than boys because she thinks that girls are better. Ex: A Republican who only looks for information that confirms what he/she believes. Ex: An Obama fan who only looks for the good he has done & ignores the bad.

28. Overconfidence Sometimes we think we know more than we actually know. Study on anagrams: People said it would take about 10 seconds, yet on average they took about 3 minutes (Goranson, 1978).

29. Sampling Bias Some members of a population are more likely to be included in a study than others Dewey/Truman 1948 Presidential elections: ▫Chicago Tribune: Dewey defeats Truman ▫Survey of voters—telephone survey

30. Descriptive/Correlational Methods: Looking for Relationships Methods used when a researcher cannot manipulate the variables under study ▫Naturalistic observation ▫Case studies ▫Surveys Allows researchers to describe patterns of behavior and discover links or associations between variables but cannot imply causation SNL census clip

31. Statistics and Research: Drawing Conclusions Statistics – using mathematics to organize, summarize, and interpret numerical data ▫Descriptive statistics: organizing and summarizing data ▫Inferential statistics: interpreting data and drawing conclusions

32. Descriptive Statistics: Measures of Central Tendency Measures of central tendency = typical or average score in a distribution Mean: arithmetic average of scores Median: score falling in the exact center Mode: most frequently occurring score ▫Which most accurately depicts the typical?

33. Figure 2.11 Measures of central tendency

34. Descriptive Statistics: Variability Variability = how much scores vary from each other and from the mean ▫Standard deviation = numerical depiction of variability  High variability in data set = high standard deviation  Low variability in data set = low standard deviation

35. Figure 2.12 Variability and the standard deviation

36. Descriptive Statistics: Correlation When two variables are related to each other, they are correlated. Correlation = numerical index of degree of relationship ▫Correlation expressed as a number between 0 and 1 ▫Can be positive or negative ▫Numbers closer to 1 (+ or -) indicate stronger relationship

37. Correlation Correlation Coefficient is a statistical measure of the relationship between two variables. When one trait or behavior accompanies another, we say the two correlate. Correlation coefficient Indicates direction of relationship (positive or negative) Indicates strength of relationship (0.00 to 1.00) r = 0.37 +

38. Figure 2.13 Positive and negative correlation

39. Figure 2.14 Interpreting correlation coefficients

40. Perfect positive correlation (+1.00) Scatterplot is a graph comprised of points that are generated by values of two variables. The slope of the points depicts the direction, while the amount of scatter depicts the strength of the relationship. Scatterplots

41. No relationship (0.00) Perfect negative correlation (-1.00) The Scatterplot on the left shows a negative correlation, while the one on the right shows no relationship between the two variables. Scatterplots

42. Data Data showing height and temperament in people.

43. Scatterplot The Scatterplot below shows the relationship between height and temperament in people. There is a moderate positive correlation of +0.63.

44. Correlation: Prediction, Not Causation Higher correlation coefficients = increased ability to predict one variable based on the other ▫SAT/ACT scores moderately correlated with first year college GPA 2 variables may be highly correlated, but not causally related ▫Foot size and vocabulary positively correlated ▫Do larger feet cause larger vocabularies? ▫The third variable problem

45. or Correlation and Causation Correlation does not mean causation!

46. Figure 2.15 Three possible causal relationships between correlated variables

47. Inferential Statistics: Interpreting Data/Drawing Conclusions Hypothesis testing: do observed findings support the hypotheses? ▫Are findings real or due to chance? Statistical significance = when the probability that the observed findings are due to chance is very low [ P ≤.05 ] ▫Very low = less than 5 chances in 100/.05 level

48. Evaluating Research: Methodological Pitfalls Sampling bias Placebo effects Distortions in self-report data: ▫Social desirability bias ▫Response set a tendency to respond to questions in a particular way (agree with everything, etc.). Experimenter bias ▫the double-blind solution Replication—repeating an experiment/study that someone else has already done Meta-analysis-- combining results from different studies to find patterns among study results

49. Figure 2.16 The relationship between the population and the sample

50. Ethics in Psychological Research: Do the Ends Justify the Means? The question of deception The question of animal research ▫Controversy among psychologists and the public Ethical standards for research: the American Psychological Association ▫Ensures both human and animal subjects are treated with dignity

51. Figure 2.17 Ethics in research

52. The Internet and Psychological Research  Internet-mediated research refers to studies in which data collection occurs over the web.  Possible Advantages  Samples that are much larger and much more diverse than the samples typically used in laboratory research  Have the potential to yield more diverse and representative samples

53. The Internet and Psychological Research Potential Disadvantages ▫Sampling bias resulting from self-selection may be a more troublesome issue in Internet- mediated research  Web users tend to be younger, brighter, and more affluent than nonusers ▫Data are collected under far less controlled conditions than in traditional studies