Chapter 1: Thinking Critically with Psychological Science

1. The Need for Psychological Science
1. Underestimate perils of intuition
1. Hindsight bias
1. Finding that something has happened makes it seem inevitable
2. 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.)
3. Errors in recollections and explanations show why we need psychological research
4. Just asking people how and why they felt/acted can be misleading-not because common sense is usually wrong, but b/c it more easily described what has happened than what will happen
5. It has been observed in various countries among both children and adults
6. Would be surprising if many of psych’s findings had not been foreseen b/c we all watch behavior
7. But sometimes intuition is wrong, research has overturned popular ideas, for ex. familiarity breeds contempt, dreams predict the future, and emotional reactions coincide with menstrual phase, and surprised us with discoveries
2. Overconfidence
1. Once people know answer, hindsight bias makes it seem obvious and they become overconfident
2. Not much better at predicting social behavior: Robert Vallone and associates (1990) had students predict, on avg. students felt 84% confident in making self-predictions, later quizzes showed their predictions were only 71% correct
3. Even when students were 100% sure of themselves, self-predictions erred 15% of the time
4. Ohio State Uni. Psych Philip Tetlock (1998, 2005) collected > 27,000 expert predictions of world events
5. Repeated findings: predictions, which experts made with 80% confidence on avg. were right less than 40% of the time
6. Even those who erred maintained confidence by noting they were “almost right”
7. *hindsight bias and overconfidence often lead us to overestimate intuition, but scientific inquiry can help sift reality from illusion
3. The Scientific Attitude
1. 1st curiosity-a passion to explore and understand  without misleading or being mislead
2. Some questions are beyond science; to answer them requires leap of faith
3. With other ideas, proof is in pudding; does it work?
4. Scientific approach long history, even Moses, thru letting facts speak for themselves: empirical approach
5. 1700s, scientists scoffed at notion that meteorites had extraterrestrial origins; 2 Yale scientists dared to deviate from conventional opinion and were right
6. Today’s truths sometimes become tomorrow’s fallacies
7. Psychologists approach behavior with curious skepticism, asking 2 questions: What do you mean? How do you know?
8. When ideas compete, skeptical testing can reveal the ones that best match the facts
9. Also need humility: an awareness of our own vulnerability to error and an openness to surprises and new perspectives
10. If test subjects don’t behave as ideas predict, then so much the worse for ideas
11. 3 attitudes: curiosity, skepticism, and humility help make modern science possible
12. Founders had religious convictions which made them humble and skeptical of human authority
13. Today some religious nuts view science as threat, but scientific revolution was led mostly by religious people acting on the idea that to love God, one had to appreciate his work
14. We are all affected by preconceived ideas, but the ideal unifies psychologists with all scientists; scientists check and recheck others’ findings and conclusions
4. Critical Thinking
1. It examines assumptions, discerns hidden values, evaluates evidence, and assesses conclusions
2. Critical thinking: thinking that does not blindly accept arguments and conclusions
3. Psychology’s critical inquiry has been open to surprising findings:
1. Big loss of brain tissue early may have small long term effects
2. Newborns recognize mom’s odor and voice
3. Can learn with brain damage but unaware of learning
4. Diverse groups have comparable levels of personal happiness
5. Electroconvulsive shock therapy is good for severe depression
4. Also debunked popular presumptions:
1. Sleepwalkers not acting out dreams
2. Past experience not verbatim
3. Most people don’t have weirdly low self-esteem and high self-esteem not all good
4. Opposites don’t attract
5. Learned=/=believed
2. How do Psychologists Ask and Answer Questions?
1. Evaluating theories
1. The Scientific Method
1. Theory: an explanation using an integrated set of principles that organizes observations and predicts behaviors or events
2. By linking facts and bridging them to deeper principles, theory offers useful summary
3. Hypothesis: a testable prediction, often implied by a theory
4. Letting us test and to reject/revise the theory, predictions give direction to research and specify what results would support/disconfirm the theory
5. Bias subjective observations, ever-present urge to see what we expect
6. To check biases, psychologists report research with operational definitions of procedures and concepts
7. Operational definition: a statement of the procedures (operations) use to define research variables; for ex. Human intelligence may be operationally defined s what an intelligence test measures
8. Operational definitions allow others to replicate original observations
9. Replication: repeating the essence of a research study, usually with different participants in different situations, to see whether basic finding extends to other participants and circumstances
10. If other researches recreate and get similar results, confidence in finding’s reliability grows
11. The scientific method: self-correcting process for asking questions and observing nature’s answers
12. Good theories explain by:
1. Organizing and linking observed facts
2. Implying hypotheses that offer testable predictions and, sometimes, practical applications
13. Research leads to revised theory that better organizes and predicts
14. Test hypotheses and refine theories using descriptive (which describe behaviors, often using case studies, surveys, or naturalistic observations), correlational (which associate different factors), and experimental (which manipulate factors to discover their effects) methods
2. Description: psychologists observe and describe people more objectively and systematically
1. The Case Study
1. Case study: an observation technique in which 1 person is studies in depth in the hope of revealing universal principles; for ex.: particular impairment after damage to certain brain region, children’s thinking, chimp capacity for understanding and language
2. Case studies often suggest directions for further study and show what can happen, but can mislead if person studied is atypical
3. *individual cases can suggest fruitful ideas; what’s true for all of us can be glimpsed in any one of us, but to discern the general truths that cover individual cases, we must use other research methods
2. The Survey
1. Survey method looks at many cases in less depth
2. 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
1. Wording effects
1. Subtle changes in order of wording can have major effects
2. Critical thinkers reflect on how the phrasing of a question might affect people’s expressed opinions
2. Random Sampling
1. Accurate picture of whole population’s attitudes and experiences-representative sample
2. *the best basis for generalizing is from a representative sample of cases
3. Population: all the cases in a group being studied, from which samples may be drawn. (Note: except for national studies, this doesn’t refer to a country’s whole population.)
4. Random sample: a sample that fairly represents a population because each member has an equal chance of inclusion
5. *before accepting survey findings, think critically: consider the sample; can’t compensate for unrepresentative sample by adding more people
3. Naturalistic Observation
1. Naturalistic observation: observing and recording behavior in naturally occurring situations without trying to manipulate and control the situation
2. Doesn’t explain, only describes
3. Still reveals, ex. We thought only humans use tools, but chimps do too; paved way for later studies of animal behavior and further expanded out understanding
4. Whiten and Byrne (1988) saw baboon pretend to be attacked so mom drive others away from its good
5. More developed a primate species’ brain, more likely display deceptive behaviors (Byrne & Corp. 2004)
6. Human behavior
1. Laugh 30x more often in social than alone, 17 muscles contort mouth and squeeze eyes, emit a series of 75-millisecond vowel-like sounds that are spaced about 1/5th of second apart (Provine 2001)
2. Mehl and Pennebaker (2003) equipped 52 students from University of Texas with tape recorders; up to 4 days, recorder captured 30 seconds of students’ waking hours every 12.5 minutes, >10,000 half-minute slices (28% talking with someone, 9%  computer keyboard)
3. Levine and Norenzayan (1999) compare pace of life in 31 countries (operational definition pace of life included walking speed, speed postal clerks completed simple request and accuracy of public clocks) life fastest paced in Japan and Western Europe and slower paced in economically less-developed countries; colder climates live at faster pace (and more prone to die from heart disease)
7. Doesn’t control for all the factors that may influence behavior
8. Provide data for correlational research
3. Correlation
1. Describing behaviors is 1st step toward predicting it, survey and naturalistic observation show us if one trait/behavior related to another
2. Correlation: a measure of the extent to which 2 factors vary together, and thus of how well either factor predicts the other
3. Statistical measures help figure how closely 2 things vary together and how well either 1 predicts the other
4. Correlation coefficient: a statistical index of the relationship between 2 things (from -1 to +1).
5. Scatterplots: a graphed cluster of dots, each of which represents the values of 2 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)
6. Perfect correlations rarely occur
7. Each dot represents scattered values of 2 variables
8. Correlation (+) if 2 sets of scores tend to rise and fall together, saying correlation is “neg” says nothing of strength or weakness
9. (+1.00) perfect positive, no relationship (0.00), (-1.00) perfect negative
10. Correlation is neg if 2 sets relate inversely
11. Stats help see what naked eye misses, case by case, see no correlation
12. *correlation coefficient helps us see the world more clearly by revealing the extent to which 2 things relate
4. *Correlation and Causation
1. Correlations help predict
2. No matter how strong the correlation, doesn’t prove cause-and-effect; 3rd factor could explain correlation
3. Association (not just correlation but also other associations verified by other non-experimental statistics) does not prove causation
4. *correlation indicates possibility of cause-effect relationship but does not prove causation
5. Illusory Correlations
1. The perception of a relationship where none exists
2. When we believe there is a relationship, we are more likely to notice and recall instances that confirm our belief
3. *when we notice random coincidences, we may forget they are random and see them as correlated and deceive ourselves by seeing what is not there
6. Perceiving Order in Random Events
1. Random sequences often don’t look random
2. Kahneman and Tversky (1972) found that most people believe HTTHTH most likely when all equally likely
3. Event with 1 out of a billion chance happens about 6 times a day
2. Experimentation
1. Experiment: a research method in which an investigator manipulates 1 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
2. Correlational research can’t control for all possible factors
3. Experiments enable that focus on the possible effects of 1 or more factors by:
1. Manipulating the factors of interest
2. Holding constant (“controlling”) other factors
4. Random Assignment
1. No single experiment is conclusive
2. Random assignment: assigning participants to experimental and control groups by chance, thus minimizing pre-existing differences between those assigned to the different groups
3. Eliminates alternative explanations by holding constant all other factors
4. If behavior changes when we vary experimental factor, then factor is having an effect
5. *unlike correlational studies, which uncover naturally occurring relationships, an experiment manipulates a factor to determine its effect
6. 1 group receives treatment and other a placebo
7. Double-blind procedure: an experimental procedure in which both the research participants and research staff are ignorant (blind) about whether the research participants have received the treatment or a placebo, commonly used in drug-evaluation studies
8. Researches can check treatment’s actual effects apart from the participants’ belief in its healing powers and the staff’s enthusiasm for its potential
9. Placebo (Latin “I shall please”) 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
10. More expensive the placebo, the better if works
11. Must control for placebo effect
12. Double blind one way to create experimental and control group
13. Experimental group: in an experiment, the group that is exposed to the treatment, that is, to one version of the independent variable
14. Control group: 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
15. By randomly assigning people to these conditions, fairly certain the 2 groups are otherwise identical; random assignment roughly equalizes the 2 groups in age, attitudes, and every other characteristic
16. With random assignment, conclude any later different between experimental and control groups will be result of treatment
5. Independent and Dependent Variables
1. Independent variable: the experimental factor that is manipulated; the variable whose effect is being studied
2. Vary independently of other factors which random assignment control
3. Dependent variable: the outcome factor;  the variable that may change in response to manipulations of the independent variable, usually behavior/mental process
4. Both variables given operational definition which specify procedures that manipulate the individual variable or measure the dependent variable
5. Distinction between random sampling (helps us generalize to a larger population) and random assignment (controls extraneous influences, which help infer cause and effect)
6. Recap. variable-anything that can vary, experiments aim to manipulate an independent variable, measure the dependent variable, and control all other variables; an experiment has at least 2 groups: an experimental and comparison/control, random assignment works to equate groups before any treatment effects
7. Experiments test effect of at least 1 independent variable (what we manipulate) on at least 1 dependent variable (the outcome we measure)
3. Statistical Reasoning in Everyday Life
1. *Doubt big, round, undocumented #s, rather than swallowing top-of-the-head estimates, focus on thinking smarter by applying simple statistical principles to everyday reasoning
2. Describing Data
1. Bar graph: make difference look big/small by how one labels vertical scale/Y-axis
2. *when viewing figures in magazines and on TV, read scale labels and note their range
3. Measures of Central Tendency
1. Next step-summarize the date using some measure of central tendency, a single score that represents a whole set of scores; problems if distribution skewed and paints inaccurate picture
2. Simplest measure-mode: the most frequently occurring score or scores in a distribution
3. Most commonly reported-mean: the arithmetic average of a distribution, obtained by adding the scores and then dividing by the # of scores
4. Median: midpoint, 50th percentile, the middle score in a distribution; half the scores are above it and half are below it
5. Ex. Income data, mean, median, and mode, very different because mean biased by few extreme scores; if Bill Gates moved to your neighborhood, mean goes up but median still same
6. *Always note which measure of central tendency is reported, then, if it is a mean, consider whether a few atypical scores could be distorting it
4. Measures of Variation
1. Helps to know something about the amount of variation in the data-how similar or diverse scores are
2. Argument derived from scores with low variability are more reliable than argument based on scores with high variability
3. Range-the difference between the highest and lowest scores in a distribution, provides only crude estimate of variation because a couple of extreme scores in otherwise uniform group will create deceptively large range
4. More useful standard for measuring how much scores deviate from another is the standard deviation-a computed measure of how much scores vary around the mean score, better gauges whether scores are packed or dispersed because it uses info from each score, computes or assembles info about how much individual scores differ from mean
5. Standard deviation=sqrt[sum of (deviations)^2/# of scores]
6. Normal curve: (normal distribution) a symmetrical, bell-shaped curve that describes the distribution of many types of data (such as the Wechsler intelligence scores); most scores fall near the mean (68% fall within 1 standard deviation of it) and fewer and fewer near the extremes
7. 95% fall within 2 standards deviations
3. Making Inferences
1. Average score in 1 group could differ from average score in another not because of any real difference but because of chance fluctuations in the people sampled
2. How confidently can we inter that an observed difference accurately estimates the true difference? We can ask how reliable and significant the difference is
3. When is an Observed Difference Reliable?
1. Representative samples better than biased samples: best basis for generalizing is from a representative sample of cases, keep in mind what population a study has sampled
2. Less-variable observations are more reliable than those that are more variable: an average is more reliable when it comes from scores with low variability
3. More cases are better than fewer: averages based on many cases are more reliable (less variable) than averages based on only a few
4. *Don’t be overly impressed by a few anecdotes, generalizations based on a few unrepresentative cases are unreliable
4. When is a Difference Significant?
1. When 2 samples are each reliable measures of their respective populations (as when each is based on many observations that have small variability), then their difference is likely to be reliable as well
2. When difference is large, even more confidence that the difference reflects real difference in their population
3. When sample averages are reliable and when difference between them is relatively large, has statistical significance-a statistical statement of how likely it is that an obtained result occurred by chance, high significance means that observed difference is probably not due to chance variation between the samples
4. Not much of finding unless the odds of it occurring by chance <5% (arbitrary criterion)
5. May be stat sig but have little practical sig, ex. 1st borns and later borns high sig tendencies for 1st borns to have higher average scores than siblings but scores differ by so little no practical importance
6. Some advocate alternative to significance testing, use other way to express effect size-its magnitude and reliability
7. *stat sig indicates the likelihood that a result will happen by chance, but doesn’t say anything about importance
4. Frequently Asked Questions About Psychology
1. Can lab experiments illuminate everyday life?
1. Lab environments intended to be simplified reality; experiment’s purpose isn’t to recreate exact behaviors but to test theoretical principles-resulting principles-not specific findings that help explain everyday behaviors, principles refined every experiment, many investigations show that principles from lab do generalize to everyday world
2. *psych’s concern is less with particular behaviors than with general principles that help explain many behaviors
2. Does behavior depend on one’s culture and gender?
1. Culture-the enduring behaviors, ideas, attitudes, and traditions shared by a group of people and transmitted from 1 generation to the next-matters
2. Culture shapes behavior-being aware of such differences can restrain assumptions that others will think/act as we do
3. Shared biological heritage unites us-same underlying processes guide people everywhere:
1. People with dyslexia exhibit same brain malfunction whether Italian/French/British
2. Variation in language may impede communication across cultures yet all language share principles of grammar and people from opposite hemispheres can communicate with smile/frown
3. People in different cultures vary in feelings of loneliness, but across cultures, loneliness is magnified by shyness, low self-esteem, and being unmarried
4. Studying people of all races/cultures helps us discern similarities and differences, human kinship and diversity
5. Gender matters: differences in what we dream, how we express and detect emotions, and in risk for alcohol dependence, depression, and eating disorders
6. Psychologically similar
7. *even when specific attitudes and behaviors vary by gender/across culture, underlying processes much the same
3. Why do psychologists study animals, and is it ethical to experiment on animals?
1. Want to understand how different species learn, think, and behave; study animals to learn about people
2. Humans experiments led to treatments, human processes seen in other mammals
3. Animals simpler, more revealing
4. Animal protection movement protests the use of animals in psychological/medical research
5. Psychology responds with examples of animal testing leading to vaccines
6. US & Canada 60%; Britain 37% okay
7. Two issues:
1. Whether right to place well-being of humans above that of animals
1. Compassion for animals vary, as does compassion for people-based on perceived similarity to us
2. Value animals according to their perceived kinship with us (ranks):
1. Primates/companion pets get top priority
2. Other mammals
3. Birds, fish, and reptiles
4. Insects
5. Draw own cut-offline
2. Priority given to well-being of animals in research: what safeguards?
1. Professional associations and funding agencies already have guidelines
1. BPS: housing under reasonably natural living conditions with companions for social animals
2. APA: ensure “comfort, health, and humane treatment” and minimize “infection, illness, and pain”
8. Animals benefitted from animal research to improve care/management in animals’ natural habitat
9. Reveal behavioral kinship with animals, experiments have led to increased empathy/protection
4. Is it ethical to experiment on people?
1. Temporary stress/deception but when necessary to justifiable end
2. Ethical principles developed by APA (1992), by BPS (1993) and psychologists international urge investigators to
1. Obtain the informed consent of potential participants
2. Protect them from harm and discomfort
3. Treat informational about individual participants confidentially
4. Fully explain research afterwards
3. Most universities today screen research proposals through ethics committee that safeguards well-being of every participant
4. Researcher-informative and considerate, participant learn something and most enjoy engagement
5. Stores research without ethics committee
5. Is psychology free of value judgments? No.
1. Values affect what we study, how we study, and how we interpret results
2. Preconceptions bias observations/interpretation
3. Words have different connotations and reflect values
4. Accept value-laden advice when ask for professional guidance
5. Psychology can deceive but intent is to enlighten
6. Psychology helps problems and speaks to our desire of nourishment/love/happiness
7. Kenneth/Mamie Phipps Clark (1947): when given choice between black/white dolls most African-Americans chose white doll, internalized anti-black prejudice