1. Unit 2: Research Methods

3. Did We Know It All Along? Hindsight Bias Hindsight Bias –“I knew it all along”

6. Overconfidence Overconfidence: we tend to think we know more than we do –How long will it take you to solve these anagrams? –Richard Goranson Study WREAT ---------- ? ETRYN------------ ? GRABE------------?

7. Overconfidence –We tend to think we know more than we do –Richard Goranson Study WREAT ---------- WATER ETRYN------------ ENTRY GRABE------------ BARGE

8. Perceiving Order in Random Events Comes from our need to make sense out of the world –Coin flip –Poker hand

9. The Scientific Attitude: Curious, Skeptical and Humble Psychology is a science & scientific inquiry is needed! Three main components –Curious eagerness –Skeptically scrutinize competing ideas –Open-minded humility before nature Hindsight bias, overconfidence & tendency to perceive patterns in random events leads us to overestimate our intuition.

10. Critical Thinking –“Smart thinking” –Elements Examines assumptions Assesses the source Discerns hidden values Confirms evidence Assesses conclusions

12. The Scientific Method Theory – explanation based on observationsTheory –“mere hunch” Hypothesis – testable predictionHypothesis –Can be confirmed or refuted Operational Definition – precise procedure or measuresOperational Definition Replication (repeat)- reproducible results with different subjects/situationsReplication

13. The Scientific Method

14. A good theory is useful if it: –Effectively organizes a range of self-reports and observations –Leads to clear hypotheses (predictions) that anyone can use to check the theory –Often stimulates research that leads to a revised theory which better predicts what we know

15. How Do We Test a Hypothesis and Refine a Theory? - Descriptive Methods using case studies, surveys or naturalistic observations - Correlational Methods - Experimental Methods

16. Description The Case Study Case Study – study one individual or groupCase Study –Hope to reveal universal truths –Problems with atypical individuals –Cannot discern general truths

17. Description: Naturalistic Observation Naturalistic Observation –Describes behavior –Does not explain behavior - Goodall

18. Description: The Survey Survey: l ooks at many cases at onceSurvey Word effects – wording is key Random sampling –Representative sample –Sampling bias: flawed sampling that produces an unrepresentative sampleSampling bias

19. Description: The Survey Sampling –PopulationPopulation –Random SampleRandom Sample

21. Correlation Correlation (correlation coefficient)Correlationcorrelation coefficient –How well does A predict B –Positive versus negative correlation –Strength of the correlation -1.0 to +1.0 –ScatterplotScatterplot

22. Correlation

27. Correlation and Causation Correlation helps predict –Does not imply cause and effect

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

30. Experimentation Experiment –Can isolate cause and effect –Control of factors Manipulation the factor (s) of interest Hold constant (“controlling”) factors

31. Experimentation Groups –Experimental GroupExperimental Group R eceives the treatment (independent variable) –Control GroupControl Group D oes not receive the treatment

32. Experimentation Randomly assigned –Eliminates alternative explanations –Equalizes the two groups –Reduces the influence of other (confounding variables) –Different from random sample random sample

33. Experimentation Blind (uninformed) –Single-Blind Procedure –Double-Blind ProcedureDouble-Blind Procedure Placebo Effect

34. Independent & Dependent Variables Independent Variable –Confounding variableConfounding variable Effect of random assignment on confounding variables Dependent Variable –What is being measured Validity & ReliabilityValidity

35. Cross-Sectional & Longitudinal Studies Cross-sectional: compares different populations at the same point in time Longitudinal: researchers conduct several observations of the same population (subjects) over a period of time, sometimes lasting many years

37. Comparing Research Methods

39. The Need for Statistics Understanding basic statistics is beneficial for everyone

40. Reliability and Validity Reliability: the extent to which an experiment or procedure yields the same result on repeated trials Validity: the degree to which a study or procedure accurately reflects or assesses the specific concept that the researcher is Attempting to measure

41. Descriptive Statistics Histogram (bar graph)Histogram –Scale labels

42. Descriptive Statistics: Histogram

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

44. Variance & Standard Deviation

45. Measures of Variability Range – order lowest to highestRange Standard Deviation – square root of varianceStandard Deviation

46. Variance & Standard Deviation

47. Standard Deviation

48. Descriptive Statistics: Measures of Variability Normal Curve

49. Measures of Variability Normal Curve

50. Flynn Effect The Flynn Effect: there is a marked increase in intelligence test score averages over time. This has been reported to happen worldwide.intelligence test When a new group of people take the previous test there is an increase in scores with the new group typically scoring well above 100 (which is the average). Explanations: better nutrition, less infectious disease, longer & more productive education, and more stimulating environments.

51. Inferential Statistics: When Is an Observed Difference Reliable? Inferential statistics Representative samples are better than biased samples Less-variable observations are more reliable than those that are more variable More cases are better than fewer

52. When Is a Difference Significant? Statistical significance –The averages are reliable –The differences between averages is relatively large –Does imply the importance of the results

53. More on Inferential Statistics… See handouts

54. The Null Hypothesis In statistics, the null hypothesis is the hypothesis that sample observations result purely from chance. The alternative hypothesis is the hypothesis that sample observations are influenced by some non-random cause. The null hypothesis = the outcome is not statistically significant, but is due to chance Researchers aim to reject the null hypothesis

55. Statistical Significance Researchers conduct experiments to achieve statistical significance. This means that the likelihood that the experimental results are due to random events (chance) is less than 5%. Results yielding a p-value of.05 are considered of statistical significance.

56. Type I and Type II Errors Type I Error: a false positive or “false alarm.” E.g. a drug doesn’t work and we say that it does –Null hypothesis states that the drug does not work –Incorrect rejection of a true null hypothesis (the drug does not work) Type II Error – a false rejection or a “miss.” E.g. a drug does work and we say that it doesn’t –Failure to reject (we accept) the false null hypothesis (that drug does not work)

58. Psychology Applied Can laboratory experiments illuminate everyday life? –The principles, not the research findings, help explain behavior Does behavior depend on one’s culture and gender? –CultureCulture –Gender

59. Ethics in Research Ethics in animal research –Reasons for using animals in research –Safeguards for animal use

60. Ethics in Research Ethics in human research –Informed consentInformed consent –Protect from harm and discomfort –Maintain confidentiality –DebriefingDebriefing

61. Hindsight Bias = the tendency to believe, after learning an outcome, that one would have foreseen it. Also known as the “I knew it all along” phenomenon.

62. Critical Thinking = thinking that does not blindly accept arguments and conclusions. Rather, it examines assumptions, discerns hidden values, evaluated evidence, and assesses conclusions.

63. Theory = an explanation using an integrated set of principles that organizes observations and predicts behaviors or events.

64. Hypothesis = a testable prediction, often implied by a theory.

65. Operational Definition = a carefully worded statement of the exact procedures (operations) used in a research study. For example, human intelligence may be operationally defined as what an intelligence test measures.

66. Replication = repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding extends to other participants and circumstances.

67. Case Study = an descriptive technique in which one individual or group is studied in depth in the hope of revealing universal principles.

68. Naturalistic Observation = observing and recording behavior in naturally occurring situations without trying to manipulate and control the situation.

69. Survey = a technique for ascertaining the self- reported attitudes or behaviors of a particular group, usually by questioning a representative, random sample of the group.

70. Sampling Bias = a flawed sampling process that produces an unrepresentative sample.

71. Population = all the cases in a group being studied, from which samples may be drawn. Note: Except for national studies, this does NOT refer to a country’s whole population.

72. Random Sample = a sample that fairly represents a population because each member has an equal chance of inclusion.

73. Correlation = a measure of the extent to which two factors change together, and thus of how well either factor predicts the other.

74. Correlation Coefficient = a statistical index of the relationship between two things (from -1.0 to +1.0).

75. Scatterplot = a graphed cluster of dots, each of which represents the values of two variables. The slope of the points suggests the direction of the relationship between the two variables. The amount of scatter suggests the strength of the correlation (little scatter indicates high correlation).

76. Illusory Correlation = the perception of a relationship where none exists.

77. Experiment = a research method in which an investigator manipulates one or more factors (independent variables) to observe the effect on some behavior or mental process (the dependent variable). By random assignment of participants, the experimenter aims to control other relevant factors.

78. Experimental Group = in an experiment, the group that is exposed to the treatment, that is, to one version of the independent variable.

79. Control Group = in an experiment, the group that is NOT exposed to the treatment; contrasts with the experimental group and serves as a comparison for evaluating the effect of the treatment.

80. Random Assigment = assigning participants to experimental and control groups by chance, thus minimizing preexisting differences between those assigned to the different groups.

81. Double-Blind Procedure = an experimental procedure in which both the research participants and the research staff are ignorant (blind) about whether the research participants have received the treatment or the placebo. Commonly used in drug-evaluation studies.

82. Placebo Effect = experimental results caused by expectations alone; any effect on behavior caused by the administration of an inert substance or condition, which the recipient assumes is an active agent. Latin for “I shall please”

83. Independent Variable = the experimental factor that is manipulated; the variable whose effect is being studied.

84. Confounding Variable = a factor other than the independent variable that might produce an effect in an experiment.

85. Dependent Variable = the outcome factor; the variable that may change in response to manipulations of the independent variable.

86. Validity = the extent to which a test or experiment measures or predicts what it is suppose to.

87. Descriptive Statistics = numerical data used to measure and describe characteristics of groups. Include measures of central tendency and measures of variability.

88. Histogram = a bar graph depicting a frequency distribution.

89. Mode = the most frequently occurring score(s) in a distribution.

90. Mean = the arithmetic average of a distribution, obtained by adding the scores and then dividing by the number of scores.

91. Median = the middle score in a distribution, half the scores are above it and half are below it.

92. Skewed Distribution = a representation of scores that lack symmetry around their average value.

93. Range = the difference between the highest and lowest score in a distribution.

94. Standard Deviation = a computed measure of how much scores vary around the mean score.

95. Normal Curve = a symmetrical, bell-shaped curve that describes the distribution of many types of data; most scored fall near the mean (68 percent fall within one standard deviation of it) and fewer and fewer near the extremes. Normal distribution

96. Inferential Statistics = numerical data that allow one to generalize – to infer from sample data the probability of something being true to a population.

97. Statistical Significance = a statistical statement of how likely it is that an obtained result occurred by chance.

98. Culture = the enduring behavior, ideas, attitudes, and traditions shared by a group of people and transmitted from one generation to the next.

99. Informed Consent = an ethical principle that research participants be told enough to enable them to choose whether they wish to participate.

100. Debriefing = the postexperimental explanation of a study, including its purpose and any deceptions, to its participants.