Although in some ways we outsmart the smartest computers, our intuition often goes awry. To err is human. Enter psychological science. With its procedures for gathering and sifting evidence, science restrains error. As we familiarize ourselves with psychology’s strategies and incorporate its underlying principles into our daily thinking, we can think smarter. Psychologists use the science of behavior and mental processes to better understand why people think, feel, and act as they do.

What About Intuition and Common Sense?

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1-7 How does our everyday thinking sometimes lead us to a wrong conclusion?

Some people suppose that psychology merely documents and dresses in jargon what people already know: “You get paid for using fancy methods to prove what my grandmother knows?” Others place their faith in human intuition: “Buried deep within each and every one of us, there is an instinctive, heart-felt awareness that provides—if we allow it to—the most reliable guide,” offered Prince Charles (2000). Today’s psychological science does document a vast intuitive mind. As we will see, our thinking, memory, and attitudes operate on two levels—conscious and unconscious—with the larger part operating off-screen, automatically. Like jumbo jets, we fly mostly on autopilot.

So, are we smart to listen to the whispers of our inner wisdom, to simply trust “the force within”? Or should we more often be subjecting our intuitive hunches to skeptical scrutiny?

This much seems certain: We often underestimate intuition’s perils. My [DM’s] geographical intuition tells me that Reno is east of Los Angeles, that Rome is south of New York, that Atlanta is east of Detroit. But I am wrong, wrong, and wrong. As novelist Madeleine L’Engle observed, “The naked intellect is an extraordinarily inaccurate instrument” (1973). Three phenomena—hindsight bias, overconfidence, and our tendency to perceive patterns in random events—illustrate why we cannot rely solely on intuition and common sense.

DID WE KNOW IT ALL ALONG? HINDSIGHT BIAS Consider how easy it is to draw the bull’s-eye after the arrow strikes. As we often say, “Hindsight is 20/20.” After the stock market drops, people say it was “due for a correction.” After the football game, we credit the coach if a “gutsy play” wins the game, and fault the coach for the “stupid play” if it doesn’t. After a war or an election, its outcome usually seems obvious. Although history may therefore seem like a series of inevitable events, the actual future is seldom foreseen. No one’s diary recorded, “Today the Hundred Years War began.”

This hindsight bias (also known as the I-knew-it-all-along phenomenon) is easy to demonstrate: Give half the members of a group some purported psychological finding, and give the other half an opposite result. Tell the first group, “Psychologists have found that separation weakens romantic attraction. As the saying goes, ‘Out of sight, out of mind.’” Ask them to imagine why this might be true. Most people can, and nearly all will then view this true finding as unsurprising.

Tell the second group the opposite: “Psychologists have found that separation strengthens romantic attraction. As the saying goes, ‘Absence makes the heart grow fonder.’” People given this untrue result can also easily imagine it, and most will also see it as unsurprising. When opposite findings both seem like common sense, there is a problem.

Such errors in our recollections and explanations show why we need psychological research. Just asking people how and why they felt or acted as they did can sometimes be misleading—not because common sense is usually wrong, but because common sense better describes what has happened than what will happen.

More than 800 scholarly papers have shown hindsight bias in people young and old from across the world (Roese & Vohs, 2012). Nevertheless, Grandma’s intuition is often right. As Yogi Berra once said, “You can observe a lot by watching.” (We have Berra to thank for other gems, such as “Nobody ever comes here—it’s too crowded,” and “If the people don’t want to come out to the ballpark, nobody’s gonna stop ’em.”) Because we’re all behavior watchers, it would be surprising if many of psychology’s findings had not been foreseen. Many people believe that love breeds happiness, for example, and they are right (we have what Chapter 10 calls a deep “need to belong”).

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OVERCONFIDENCE We humans tend to think we know more than we do. Asked how sure we are of our answers to factual questions (Is Boston north or south of Paris?), we tend to be more confident than correct.² Or consider these three anagrams, which Richard Goranson (1978) asked people to unscramble:

About how many seconds do you think it would have taken you to unscramble each of these? Knowing the answers tends to make us overconfident. (Surely the solution would take only 10 seconds or so.) In reality, the average problem solver spends 3 minutes, as you also might, given a similar anagram without the solution: OCHSA.³

Are we any better at predicting social behavior? Psychologist Philip Tetlock (1998, 2005) collected more than 27,000 expert predictions of world events, such as the future of South Africa or whether Quebec would separate from Canada. His repeated finding: These predictions, which experts made with 80 percent confidence on average, were right less than 40 percent of the time. Nevertheless, even those who erred maintained their confidence by noting they were “almost right”: “The Québécois separatists almost won the secessionist referendum.”

PERCEIVING ORDER IN RANDOM EVENTS We have a built-in eagerness to make sense of our world. People see a face on the Moon, hear Satanic messages in music, or perceive the Virgin Mary’s image on a grilled cheese sandwich. Even in random data, we often find patterns, because—here’s a curious fact of life—random sequences often don’t look random (Falk et al., 2009; Nickerson, 2002, 2005). Flip a coin 50 times and you may be surprised at the streaks of heads and tails. In actual random sequences, patterns and streaks (such as repeating digits) occur more often than people expect (Oskarsson et al., 2009).

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Some happenings, such as winning the lottery twice, seem so extraordinary that we find it difficult to conceive an ordinary, chance-related explanation. “But with a large enough sample, any outrageous thing is likely to happen,” note statisticians Persi Diaconis and Frederick Mosteller (1989). An event that happens to but 1 in 1 billion people every day occurs about 7 times a day, more than 2500 times a year.

The point to remember: Hindsight bias, overconfidence, and our tendency to perceive patterns in random events often lead us to overestimate our intuition. But scientific inquiry can help us sift reality from illusion.

Psychologists arm their scientific attitude with the scientific method—a self-correcting process for evaluating ideas with observation and analysis. In its attempt to describe and explain human nature, psychological science welcomes hunches and plausible-sounding theories. And it puts them to the test. If a theory works—if the data support its predictions—so much the better for that theory. If the predictions fail, the theory will be revised or rejected.

Constructing Theories

1-8 How do theories advance psychological science?

In everyday conversation, we often use theory to mean “mere hunch.” Someone might, for example, discount evolution as “only a theory”—as if it were mere speculation. In science, a theory explains behaviors or events by offering ideas that organize what we have observed. By organizing isolated facts, a theory simplifies. By linking facts with deeper principles, a theory offers a useful summary. As we connect the observed dots, a coherent picture emerges.

A theory about sleep effects on memory, for example, helps us organize countless sleep-related observations into a short list of principles. Imagine that we observe over and over that people with good sleep habits tend to answer questions accurately in class and do well at test time. We might therefore theorize that sleep improves memory. So far so good: Our principle neatly summarizes a list of facts about the effects of a good night’s sleep on memory.

Yet no matter how reasonable a theory may sound—and it does seem reasonable to suggest that sleep could improve memory—we must put it to the test. A good theory produces testable predictions, called hypotheses. Such predictions specify what results (what behaviors or events) would support the theory and what results would oppose it. To test our theory about the effects of sleep on memory, our hypothesis might be that when sleep deprived, people will remember less from the day before. To test that hypothesis, we might assess how well people remember course materials they studied before a good night’s sleep, or before a shortened night’s sleep (FIGURE 1.2 below). The results will either support our theory or lead us to revise or reject it.

Our theories can bias our observations. Having theorized that better memory springs from more sleep, we may see what we expect: We may perceive sleepy people’s comments as less insightful. The urge to see what we expect is ever-present, both inside and outside the laboratory, as when people’s views of climate change influence their interpretation of local weather events.

As a check on their biases, psychologists report their research with precise operational definitions of procedures and concepts. Sleep deprived, for example, might be defined as “X hours less” than one’s natural sleep. Using these carefully worded statements, others can replicate (repeat) the original observations with different participants, materials, and circumstances. If they get similar results, confidence in the finding’s reliability grows. The first study of hindsight bias aroused psychologists’ curiosity. Now, after many successful replications with different people and questions, we feel sure of the phenomenon’s power. Although “mere replications” of others’ research are unglamorous—they seldom make headline news—today’s science is placing greater value on replication studies. International research teams are repeating high-profile studies. In one project, which attempted replications of 13 studies, researchers convincingly replicated 10 findings with similar or greater effects. They replicated one with a weaker effect. And they failed to replicate two studies (Klein et al., 2014). Such replication forms an essential part of good science. Replication = confirmation.

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In the end, our theory will be useful if it (1) organizes observations and (2) implies predictions that anyone can use to check the theory or to derive practical applications. (Does people’s sleep predict their retention?) Eventually, our research may (3) stimulate further research that leads to a revised theory that better organizes and predicts.

As we will see next, we can test our hypotheses and refine our theories using descriptive methods (which describe behaviors, often through case studies, naturalistic observations, or surveys), correlational methods (which associate different factors), and experimental methods (which manipulate factors to discover their effects). To think critically about popular psychology claims, we need to understand these methods and know what conclusions they allow.

Description

1-9 How do psychologists use case studies, naturalistic observations, and surveys to observe and describe behavior, and why is random sampling important?

The starting point of any science is description. In everyday life, we all observe and describe people, often drawing conclusions about why they act as they do. Professional psychologists do much the same, though more objectively and systematically, through

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THE CASE STUDY Among the oldest research methods, the case study examines one individual or group in depth in the hope of revealing things true of us all. Some examples: Much of our early knowledge about the brain came from case studies of individuals who suffered a particular impairment after damage to a certain brain region. Jean Piaget taught us about children’s thinking after carefully observing and questioning only a few children. Studies of only a few chimpanzees revealed their capacity for understanding and language. Intensive case studies are sometimes very revealing, and they often suggest directions for further study.

But atypical individual cases may mislead us. Both in our everyday lives and in science, unrepresentative information can lead to mistaken conclusions. Indeed, anytime a researcher mentions a finding (Smokers die younger: 95 percent of men over 85 are nonsmokers) someone is sure to offer a contradictory anecdote (Well, I have an uncle who smoked two packs a day and lived to be 89). Dramatic stories and personal experiences (even psychological case examples) command our attention and are easily remembered. Journalists understand that, and often begin their articles with personal stories. Stories move us. But stories can mislead. Which of the following do you find more memorable? (1) “In one study of 1300 dream reports concerning a kidnapped child, only 5 percent correctly envisioned the child as dead” (Murray & Wheeler, 1937). (2) “I know a man who dreamed his sister was in a car accident, and two days later she died in a head-on collision!” Numbers can be numbing, but the plural of anecdote is not evidence. A psychologist’s single case of someone who reportedly changed from gay to straight is not evidence that sexual orientation is a choice. As psychologist Gordon Allport (1954, p. 9) said, “Given a thimbleful of [dramatic] facts we rush to make generalizations as large as a tub.”

The point to remember: Individual cases can suggest fruitful ideas. What’s true of all of us can be glimpsed in any one of us. But to discern the general truths that cover individual cases, we must employ other research methods.

NATURALISTIC OBSERVATION A second descriptive method records behavior in natural environments. These naturalistic observations range from watching chimpanzee societies in the jungle, to videotaping and analyzing parent-child interactions in different cultures, to recording racial differences in students’ self-seating patterns in a school lunchroom.

Naturalistic observation has mostly been “small science”—science that can be done with pen and paper rather than fancy equipment and a big budget (Provine, 2012). But new technologies, such as smart-phone apps, body-worn sensors, and social media, are enabling “big data” naturalistic observation. Using such tools, researchers can track people’s location, activities, and opinions—without interference. The billions of people on Facebook, Twitter, and Google have also created a huge but sometimes controversial new opportunity for big-data naturalistic observation. Meanwhile, the data pour in. One research team studied the ups and downs of human moods by counting positive and negative words in 504 million Twitter messages from 84 countries (Golder & Macy, 2011). As FIGURE 1.3 shows, people seem happier on weekends, shortly after arising, and in the evenings. (Are late Saturday evenings often a happy time for you, too?) Another study found that the proportion of negative emotion (especially anger-related) words in 148 million tweets from 1347 U.S. counties predicted the counties’ heart disease rates, and did so even better than other predictors such as smoking and obesity (Eichstaedt et al., 2015).

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Like the case study, naturalistic observation does not explain behavior. It describes it. Nevertheless, descriptions can be revealing. We once thought, for example, that only humans use tools. Then naturalistic observation revealed that chimpanzees sometimes insert a stick in a termite mound and withdraw it, eating the stick’s load of termites. Such unobtrusive naturalistic observations paved the way for later studies of animal thinking, language, and emotion, which further expanded our understanding of our fellow animals. Thanks to researchers’ observations, we know that chimpanzees and baboons use deception: Psychologists repeatedly saw one young baboon pretending to have been attacked by another as a tactic to get its mother to drive the other baboon away from its food. “Observations, made in the natural habitat, helped to show that the societies and behavior of animals are far more complex than previously supposed,” chimpanzee observer Jane Goodall noted (1998).

Naturalistic observations also illuminate human behavior. Here are three findings you might enjoy:

Naturalistic observation offers interesting snapshots of everyday life, but it does so without controlling for all the factors that may influence behavior. It’s one thing to observe the pace of life in various places, but another to understand what makes some people walk faster than others. Even so, the observation of natural everyday behavior is an important part of psychological science.

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THE SURVEY A survey looks at many cases in less depth by asking people to report their behavior or opinions. Questions about everything from sexual practices to political opinions are put to the public. In recent surveys:

But asking questions is tricky, and the answers often depend on question wording and respondent selection.

WORDING EFFECTS Even subtle changes in the order or wording of questions can have major effects. People are much more approving of “aid to the needy” than of “welfare,” of “affirmative action” than of “preferential treatment,” of “not allowing” televised cigarette ads and pornography than of “censoring” them, and of “revenue enhancers” than of “taxes.” Because wording is such a delicate matter, critical thinkers will reflect on how the phrasing of a question might affect people’s expressed opinions.

RANDOM SAMPLING In everyday thinking, we tend to generalize from cases we observe, especially vivid cases. Given (a) a statistical summary of a professor’s student evaluations and (b) the vivid comments of a biased sample (two irate students), an administrator’s impression of the professor may be influenced as much by the two unhappy students as by the many favorable evaluations in the statistical summary. The temptation to ignore the sampling bias and to generalize from a few vivid but unrepresentative cases is nearly irresistible.

So how do you obtain a representative sample of, say, the students at your college or university? It’s not always possible to survey the whole group you want to study and describe. How could you choose a group that would represent the total student population? Typically, you would seek a random sample, in which every person in the total group has an equal chance of being included in the sample group. You might number the names in the general student listing and then use a random number generator to pick your survey participants. (Sending each student a questionnaire wouldn’t work because the conscientious people who returned it would not be a random sample.) Large representative samples are better than small ones, but a small representative sample of 100 is better than an unrepresentative sample of 500.

Political pollsters sample voters in national election surveys just this way. Using some 1500 randomly sampled people, drawn from all areas of a country, they can provide a remarkably accurate snapshot of the nation’s opinions. Without random sampling (also called random selection), large samples—including unrepresentative call-in phone samples and TV or website polls—often give misleading results.

The point to remember: Before accepting survey findings, think critically. Consider the sample. The best basis for generalizing is from a representative sample. You cannot compensate for an unrepresentative sample by simply adding more people.

Correlation

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1-10 What are positive and negative correlations, and why do they enable prediction but not cause-effect explanation?

Describing behavior is a first step toward predicting it. Naturalistic observations and surveys often show us that one trait or behavior relates to another. In such cases, we say the two correlate. A statistical measure (the correlation coefficient) indicates how closely two things vary together, and thus how well either one predicts the other. Knowing how much aptitude test scores correlate with school success tells us how well the scores predict school success.

A positive correlation (above 0 to +1.00) indicates a direct relationship, meaning that two things increase together or decrease together. For example, height and weight are positively correlated.

A negative correlation (below 0 to −1.00) indicates an inverse relationship: As one thing increases, the other decreases. The weekly number of hours spent in TV watching and video gaming correlates negatively with grades. Negative correlations could go as low as −1.00, which means that, like people on opposite ends of a teeter-totter, one set of scores goes down precisely as the other goes up.

Though informative, psychology’s correlations usually explain only part of the variation among individuals. As we will see, there is a positive correlation between parents’ abusiveness and their children’s later abusiveness when they become parents. But this does not mean that most abused children become abusive. The correlation simply indicates a statistical relationship: Most abused children do not grow into abusers, but nonabused children are even less likely to become abusive. Correlations point us toward predictions, but usually imperfect ones.

The point to remember: A correlation coefficient helps us see the world more clearly by revealing the extent to which two things relate.

CORRELATION AND CAUSATION Consider some recent newsworthy correlations:

What shall we make of these correlations? Do they indicate that students would achieve more if their parents supported them less? That stopping smoking would improve mental health? That abstaining from video games would make reckless teen drivers more responsible?

No, because such correlations do not come with built-in cause-effect arrows. But correlations do help us predict. An example: Self-esteem correlates negatively with (and therefore predicts) depression. (The lower people’s self-esteem, the more they are at risk for depression.) So, does low self-esteem cause depression? If, based on the correlational evidence, you assume that it does, you have much company. A nearly irresistible thinking error is assuming that an association, sometimes presented as a correlation coefficient, proves causation. But no matter how strong the relationship, it does not. As FIGURE 1.4 indicates, we’d get the same negative correlation between self-esteem and depression if depression caused people to be down on themselves, or if some third factor—such as heredity or distressing events—caused both low self-esteem and depression.

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This point is so important—so fundamental to thinking smarter with psychology—that it merits another example. A survey of over 12,000 adolescents found that the more teens feel loved by their parents, the less likely they are to behave in unhealthy ways—having early sex, smoking, abusing alcohol and drugs, exhibiting violence (Resnick et al., 1997). “Adults have a powerful effect on their children’s behavior right through the high school years,” gushed an Associated Press (AP) story reporting the finding. But again, correlations come with no built-in cause-effect arrow. The AP could as well have reported, “Well-behaved teens feel their parents’ love and approval; out-of-bounds teens more often think their parents are disapproving.”

The point to remember (turn the volume up here): Correlation does not prove causation. Correlation indicates the possibility of a cause-effect relationship but does not prove such. Remember this principle and you will be wiser as you read and hear news of scientific studies.

Experimentation

1-11 What are the characteristics of experimentation that make it possible to isolate cause and effect?

Happy are they, remarked the Roman poet Virgil, “who have been able to perceive the causes of things.” How might psychologists perceive causes in correlational studies, such as the correlation between breast feeding and intelligence? Is breast really best?

Intelligence scores of children who were breast-fed as infants are somewhat higher than the scores of children who were bottle-fed (Angelsen et al., 2001; Mortensen et al., 2002; Quinn et al., 2001). Moreover, the longer they breast-feed, the higher their later IQ scores (Jedrychowski et al., 2012).

What do such findings mean? Do the nutrients of mother’s milk, as some researchers believe, contribute to brain development? Or do smarter mothers have smarter children? (Breast-fed children tend to be healthier and higher achieving than other children. But their bottle-fed siblings, born and raised in the same families, tend to be similarly healthy and high achieving [Colen & Ramey, 2014].) To find answers to such questions—to isolate cause and effect—researchers can experiment. Experiments enable researchers to isolate the effects of one or more factors by (1) manipulating the factors of interest and (2) holding constant (controlling) other factors. To do so, they often create an experimental group, in which people receive the treatment, and a contrasting control group whose members do not receive the treatment. To minimize any preexisting differences between the two groups, researchers randomly assign people to the two conditions. Random assignment—whether with a random numbers table or flip of the coin—effectively equalizes the two groups. If one-third of the volunteers for an experiment can wiggle their ears, then about one-third of the people in each group will be ear wigglers. So, too, with ages, attitudes, and other characteristics, which will be similar in the experimental and control groups. Thus, if the groups differ at the experiment’s end, we can surmise that the treatment had an effect.

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To experiment with breast feeding, one research team randomly assigned some 17,000 Belarus newborns and their mothers either to a control group given normal pediatric care, or to an experimental group that promoted breast feeding, thus increasing expectant mothers’ breast-feeding intentions (Kramer et al., 2008). At 3 months of age, 43 percent of the experimental group infants were being exclusively breast-fed, as were 6 percent in the control group. At age 6, when nearly 14,000 of the children were restudied, those who had been in the breast-feeding-promotion group had intelligence test scores averaging six points higher than their control group counterparts.

With parental permission, one British research team directly experimented with breast milk. They randomly assigned 424 hospitalized premature infants either to formula feedings or to breast-milk feedings (Lucas et al., 1992). Their finding: For premature infants’ developing intelligence, breast was best. On intelligence tests taken at age 8, those nourished with breast milk scored significantly higher than those who were formula-fed.

No single experiment is conclusive, of course. But randomly assigning participants to one feeding group or the other effectively eliminated all factors except nutrition. This supported the conclusion that for developing intelligence, breast is indeed best. If test performance changes when we vary infant nutrition, then we infer that nutrition matters.

The point to remember: Unlike correlational studies, which uncover naturally occurring relationships, an experiment manipulates a factor to determine its effect.

Consider, then, how we might assess therapeutic interventions. Our tendency to seek new remedies when we are ill or emotionally down can produce misleading testimonies. If three days into a cold we start taking vitamin C tablets and find our cold symptoms lessening, we may credit the pills rather than the cold naturally subsiding. In the 1700s, bloodletting seemed effective. People sometimes improved after the treatment; when they didn’t, the practitioner inferred the disease was too advanced to be reversed. So, whether or not a remedy is truly effective, enthusiastic users will probably endorse it. To determine its effect, we must control for other factors.

And that is precisely how investigators evaluate new drug treatments and new methods of psychological therapy (Chapter 15). They randomly assign participants either to the group receiving a treatment (such as a medication), or to a group receiving a pseudotreatment—an inert placebo (perhaps a pill with no drug in it). The participants are often blind (uninformed) about what treatment, if any, they are receiving. If the study is using a double-blind procedure, neither the participants nor those who administer the drug or placebo and collect the data will know which group is receiving the treatment.

In double-blind studies, researchers check a treatment’s actual effects apart from the participants’ and the staff’s belief in its healing powers. Just thinking you are getting a treatment can boost your spirits, relax your body, and relieve your symptoms. This placebo effect is well documented in reducing pain, depression, and anxiety (Kirsch, 2010). Athletes have run faster when given a supposed performance-enhancing drug (McClung & Collins, 2007). Drinking decaf coffee has boosted vigor and alertness—for those who thought it had caffeine in it (Dawkins et al., 2011). People have felt better after receiving a phony mood-enhancing drug (Michael et al., 2012). And the more expensive the placebo, the more “real” it seems to us—a fake pill that costs $2.50 works better than one costing 10 cents (Waber et al., 2008). A pain-reducing placebo effect, if repeatedly experienced, can persist. Even when people learn they received a placebo, they continue to report reduced pain (Schafer et al., 2015). To know how effective a therapy really is, researchers must control for a possible placebo effect.

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INDEPENDENT AND DEPENDENT VARIABLES Here is an even more potent example: The drug Viagra was approved for use after 21 clinical trials. One trial was an experiment in which researchers randomly assigned 329 men with erectile disorder to either an experimental group (Viagra takers) or a control group (placebo takers given an identical-looking pill). The procedure was double-blind—neither the men nor the person giving them the pills knew what they were receiving. The result: At peak doses, 69 percent of Viagra-assisted attempts at intercourse were successful, compared with 22 percent for men receiving the placebo (Goldstein et al., 1998). Viagra performed.

This simple experiment manipulated just one factor: the drug dosage (none versus peak dose). We call this experimental factor the independent variable because we can vary it independently of other factors, such as the men’s age, weight, and personality. Other factors which could influence a study’s results are called confounding variables. Random assignment controls for possible confounding variables.

Experiments examine the effect of one or more independent variables on some measurable behavior, called the dependent variable because it can vary depending on what takes place during the experiment. Both variables are given precise operational definitions, which specify the procedures that manipulate the independent variable (in this study, the exact drug dosage and timing) or measure the dependent variable (the questions that assessed the men’s responses). These definitions answer the “What do you mean?” question with a level of precision that enables others to replicate the study. (See FIGURE 1.5 for the British breast milk experiment’s design.)

Let’s pause to check your understanding using a simple psychology experiment: To test the effect of perceived ethnicity on the availability of rental housing, Adrian Carpusor and William Loges (2006) sent identically worded e-mail inquiries to 1115 Los Angeles-area landlords. The researchers varied the ethnic connotation of the sender’s name and tracked the percentage of positive replies (invitations to view the apartment in person). “Patrick McDougall,” “Said Al-Rahman,” and “Tyrell Jackson” received, respectively, 89 percent, 66 percent, and 56 percent invitations.

Experiments can also help us evaluate social programs. Do early childhood education programs boost impoverished children’s chances for success? What are the effects of different antismoking campaigns? Do school sex-education programs reduce teen pregnancies? To answer such questions, we can experiment: If an intervention is welcomed but resources are scarce, we could use a lottery to randomly assign some people (or regions) to experience the new program and others to a control condition. If later the two groups differ, the intervention’s effect will be supported (Passell, 1993).

Let’s recap. A variable is anything that can vary (infant nutrition, intelligence, TV exposure—anything within the bounds of what is feasible and ethical). Experiments aim to manipulate an independent variable, measure a dependent variable, and control confounding variables. An experiment has at least two different conditions: an experimental condition and a comparison or control condition. Random assignment works to minimize preexisting differences between the groups before any treatment effects occur. In this way, an experiment tests the effect of at least one independent variable (what we manipulate) on at least one dependent variable (the outcome we measure).

TABLE 1.2 compares the features of psychology’s main research methods. You will read later about other research designs, including cross-sectional and longi-tudinal research, and twin studies. To help you understand how researchers design their studies, we have created activities that invite you to play the role of researcher (see Thinking Critically About Research Design: How Would You Know?)

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Predicting Real Behavior

1-12 Can laboratory experiments illuminate everyday life?

When you see or hear about psychological research, do you ever wonder whether people’s behavior in the lab will predict their behavior in real life? Does detecting the blink of a faint red light in a dark room say anything useful about flying a plane at night? After viewing a violent, sexually explicit film, does an aroused man’s increased willingness to push buttons that he thinks will electrically shock a woman really say anything about whether violent pornography makes a man more likely to abuse a woman?

Before you answer, consider: The experimenter intends the laboratory environment to be a simplified reality—one that simulates and controls important features of everyday life. Just as a wind tunnel lets airplane designers re-create airflow forces under controlled conditions, a laboratory experiment lets psychologists re-create psychological forces under controlled conditions.

An experiment’s purpose is not to re-create the exact behaviors of everyday life, but to test theoretical principles (Mook, 1983). In aggression studies, deciding whether to push a button that delivers a noise blast may not be the same as slapping someone in the face, but the principle is the same. It is the resulting principles—not the specific findings—that help explain everyday behaviors.

When psychologists apply laboratory research on aggression to actual violence, they are applying theoretical principles of aggressive behavior, principles refined through many experiments. Similarly, it is the principles of the visual system, developed from experiments in artificial settings (such as looking at red lights in the dark), that researchers apply to more complex behaviors such as night flying. And many investigations have demonstrated that principles derived in the laboratory do typically generalize to the everyday world (Anderson et al., 1999).

The point to remember: Psychological science focuses less on particular behaviors than on seeking general principles that help explain many behaviors.

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1-13 Why do psychologists study animals, and what ethical guidelines safeguard human and animal research participants? How do human values influence psychology?

We have reflected on how a scientific approach can restrain biases. We have seen how case studies, naturalistic observations, and surveys help us describe behavior. We have established how correlational studies assess the association between two factors, which indicates how well one thing predicts another. We have examined the logic that underlies experiments, which use control conditions and random assignment of participants to isolate the effects of an independent variable on a dependent variable.

Yet, even knowing this much, you may still be approaching psychology with a mixture of curiosity and apprehension. So before we plunge in, let’s entertain some common questions about psychology’s ethics and values.

Protecting Research Participants

STUDYING AND PROTECTING ANIMALS Many psychologists study nonhuman animals because they find them fascinating. They want to understand how different species learn, think, and behave. Psychologists also study animals to learn about people. We humans are not like animals; we are animals, sharing a common biology. Animal experiments have therefore led to treatments for human diseases—insulin for diabetes, vaccines to prevent polio and rabies, transplants to replace defective organs.

Humans are more complex, but the same processes by which we learn are present in rats, monkeys, and even sea slugs. The simplicity of the sea slug’s nervous system is precisely what makes it so revealing of the neural mechanisms of learning. Sharing such similarities, should we respect rather than experiment on our animal relatives? The animal protection movement protests the use of animals in psychological, biological, and medical research.

Out of this heated debate, two issues emerge. The basic one is whether it is right to place the well-being of humans above that of other animals. In experiments on stress and cancer, is it right that mice get tumors in the hope that people might not? Should some monkeys be exposed to an HIV-like virus in the search for an AIDS vaccine? Is our use and consumption of other animals as natural as the behavior of carnivorous hawks, cats, and whales? (Humans raise and slaughter 56 billion animals a year [Worldwatch Institute, 2013].) Or not?

Second, if we do give human life first priority, what safeguards should protect the well-being of animals in research? In one survey of animal researchers, 98 percent supported government regulations protecting primates, dogs, and cats, and 74 percent supported regulations providing for the humane care of rats and mice (Plous & Herzog, 2000). Many professional associations and funding agencies already have such guidelines. Most universities screen research proposals, often through an animal care ethics committee, and laboratories are regulated and inspected. British Psychological Society (BPS) guidelines call for housing animals under reasonably natural living conditions, with companions for social animals (Lea, 2000). American Psychological Association (APA) guidelines state that researchers must ensure the “comfort, health, and humane treatment” of animals and minimize “infection, illness, and pain” (APA, 2002).

Animals have themselves benefited from animal research. One Ohio team of research psychologists measured stress hormone levels in samples of millions of dogs brought each year to animal shelters. They devised handling and stroking methods to reduce stress and ease the dogs’ transition to adoptive homes (Tuber et al., 1999). Other studies have helped improve care and management in animals’ natural habitats. By revealing our behavioral kinship with animals and the remarkable intelligence of chimpanzees, gorillas, and other animals, experiments have also led to increased empathy and protection for them. At its best, a psychology concerned for humans and sensitive to animals serves the welfare of both.

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STUDYING AND PROTECTING HUMANS What about human participants? Does the image of white-coated scientists seeming to deliver electric shocks trouble you? Actually, most psychological studies are free of such stress. With people, blinking lights, flashing words, and pleasant social interactions are more common. Moreover, psychology’s experiments are mild compared with the stress and humiliation often inflicted in the modern “experiments” of reality television. In one episode of The Bachelor, a man dumped his new fiancée—on camera, at the producers’ request—for the woman who earlier had finished second (Collins, 2009).

Occasionally, researchers do temporarily stress or deceive people, but only when they believe it is essential to a justifiable end, such as understanding and controlling violent behavior or studying mood swings. Some experiments won’t work if participants know everything beforehand. (Wanting to be helpful, the participants might try to confirm the researcher’s predictions.)

The ethics codes of the APA and the BPS urge researchers to (1) obtain human participants’ informed consent before the experiment, (2) protect participants from greater-than-usual harm and discomfort, (3) keep information about individual participants confidential, and (4) fully debrief people (explain the research afterward). Moreover, university ethics committees screen research proposals and safeguard participants’ well-being.

Values in Research

Values affect what we study, how we study it, and how we interpret results. Researchers’ values influence their choice of topics. Should we study worker productivity or worker morale? Sex discrimination or gender differences? Conformity or independence? Values can also color “the facts.” As we noted earlier, our preconceptions can bias our observations and interpretations; sometimes we see what we want or expect to see (FIGURE 1.6).

In psychology and in everyday speech, labels describe and labels evaluate: One person’s rigidity is another’s consistency. One person’s faith is another’s fanaticism. One country’s enhanced interrogation techniques become torture when practiced by its enemies. Our labeling someone as firm or stubborn, careful or picky, discreet or secretive reveals our own attitudes.

Popular applications of psychology also contain hidden values. If you defer to “professional” guidance about how to live—how to raise children, how to achieve self-fulfillment, how to respond to sexual feelings, how to get ahead at work—you are accepting value-laden advice. A science of behavior and mental processes can help us reach our goals. But it cannot decide what those goals should be.

Knowledge transforms us. Learning about the solar system and the germ theory of disease alters the way people think and act. Learning about psychology’s findings also changes people: They less often judge psychological disorders as moral failings, treatable by punishment and ostracism. They less often regard and treat women as men’s mental inferiors. They less often view and raise children as ignorant, willful beasts in need of taming. “In each case,” noted Morton Hunt (1990, p. 206), “knowledge has modified attitudes, and, through them, behavior.” Once aware of psychology’s well-researched ideas—about how body and mind connect, how a child’s mind grows, how we construct our perceptions, how we remember (and misremember) our experiences, how people across the world differ (and are alike)—your mind may never again be quite the same.

But bear in mind psychology’s limits. Don’t expect it to answer the ultimate questions, such as those posed by Russian novelist Leo Tolstoy (1904): “Why should I live? Why should I do anything? Is there in life any purpose which the inevitable death that awaits me does not undo and destroy?”

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Although many of life’s significant questions are beyond psychology, some very important ones are illuminated by even a first psychology course. Through painstaking research, psychologists have gained insights into brain and mind, dreams and memories, depression and joy. Even the unanswered questions can renew our sense of mystery about “things too wonderful” for us yet to understand. Moreover, your study of psychology can help teach you how to ask and answer important questions—how to think critically as you evaluate competing ideas and claims.

If some people see psychology as merely common sense, others have a different concern—that it is becoming dangerously powerful. Is it an accident that astronomy is the oldest science and psychology the youngest? To some, exploring the external universe seems far safer than exploring our own inner universe. Might psychology, they ask, be used to manipulate people?

Knowledge, like all power, can be used for good or evil. Nuclear power has been used to light up cities—and to demolish them. Persuasive power has been used to educate people—and to deceive them. Although psychology does have the power to deceive, its purpose is to enlighten. Every day, psychologists explore ways to enhance learning, creativity, and compassion. Psychology speaks to many of our world’s great problems—war, overpopulation, prejudice, family crises, crime—all of which involve attitudes and behaviors. Psychology also speaks to our deepest longings—for nourishment, for love, for happiness. Psychology cannot address all of life’s great questions, but it speaks to some mighty important ones.

1-14 How can psychological principles help you learn and remember?

Do you, like most students, assume that the way to cement your new learning is to reread? What helps even more—and what this book therefore encourages—is repeated self-testing and rehearsal of previously studied material. Memory researchers Henry Roediger and Jeffrey Karpicke (2006) call this phenomenon the testing effect. (It is also sometimes called the retrieval practice effect or test-enhanced learning.) They note that “testing is a powerful means of improving learning, not just assessing it.” In one of their studies, students recalled the meaning of 40 previously learned Swahili words much better if tested repeatedly than if they spent the same time restudying the words (Karpicke & Roediger, 2008). Across many other studies, including in college classrooms, frequent quizzing and self-testing has boosted students’ retention (Pennebaker et al., 2013; Rowland, 2014).

As you will see in Chapter 8, to master information you must actively process it. Your mind is not like your stomach, something to be filled passively; it is more like a muscle that grows stronger with exercise. Countless experiments reveal that people learn and remember best when they put material in their own words, rehearse it, and then retrieve and review it again.

The SQ3R study method incorporates these principles (McDaniel et al., 2009; Robinson, 1970). SQ3R is an acronym for its five steps: Survey, Question, Read, Retrieve,⁴ Review.

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To study a chapter, first survey, taking a bird’s-eye view. Scan the headings, and notice how the chapter is organized.

Before you read each main section, try to answer its numbered Learning Objective Question (for this section: “How can psychological principles help you learn and remember?”). Roediger and Bridgid Finn (2009) have found that “trying and failing to retrieve the answer is actually helpful to learning.” Those who test their understanding before reading, and discover what they don’t yet know, will learn and remember better.

Then read, actively searching for the answer to the question. At each sitting, read only as much of the chapter (usually a single main section) as you can absorb without tiring. Read actively and critically. Ask questions. Take notes. Make the ideas your own: How does what you’ve read relate to your own life? Does it support or challenge your assumptions? How convincing is the evidence?

Having read a section, retrieve its main ideas. “Active retrieval promotes meaningful learning,” says Karpicke (2012). So test yourself. This will help you figure out what you know. Moreover, the testing itself will help you learn and retain the information more effectively. Even better, test yourself repeatedly. To facilitate this, we offer periodic Retrieve It opportunities throughout each chapter (see, for example, the questions in this chapter). After trying to answer these questions yourself, you can check the answers, and reread as needed.

Finally, review: Read over any notes you have taken, again with an eye on the chapter’s organization, and quickly review the whole chapter. Write or say what a concept is before rereading to check your understanding.

Survey, question, read, retrieve, review. We have organized this book’s chapters to facilitate your use of the SQ3R study system. Each chapter begins with an outline that aids your survey. Headings and Learning Objective Questions suggest issues and concepts you should consider as you read. The material is organized into sections of readable length. The Retrieve It questions will challenge you to retrieve what you have learned, and thus better remember it. The end-of-section Review includes the collected Learning Objective Questions and key terms for self-testing. Additional self-test questions in a variety of formats appear together, organized by section, at the end of each chapter, with answers available once question has been answered.

Four additional study tips may further boost your learning:

Distribute your study time. One of psychology’s oldest findings is that spaced practice promotes better retention than does massed practice. You’ll remember material better if you space your practice time over several study periods—perhaps one hour a day, six days a week—rather than cram it into one week-long (or all night) study blitz. For example, rather than trying to read an entire chapter in a single sitting, read just one main section and then turn to something else. Interleaving your study of psychology with your study of other subjects will boost your long-term retention and will protect against overconfidence (Kornell & Bjork, 2008; Taylor & Rohrer, 2010).

Spacing your study sessions requires a disciplined approach to managing your time. Richard O. Straub explains time management in a helpful preface at the beginning of this text.

Learn to think critically. Whether you are reading or in class, note people’s assumptions and values. What perspective or bias underlies an argument? Evaluate evidence. Is it anecdotal? Or is it based on informative experiments? Assess conclusions. Are there alternative explanations?

Process class information actively. Listen for a lecture’s main ideas and sub-ideas. Write them down. Ask questions during and after class. In class, as in your private study, process the information actively and you will understand and retain it better. As psychologist William James urged a century ago, “No reception without reaction, no impression without … expression.” Make the information your own. Take notes in your own words. Relate what you read to what you already know. Tell someone else about it. (As any teacher will confirm, to teach is to remember.)

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Overlearn. Psychology tells us that overlearning improves retention. We are prone to overestimating how much we know. You may understand a chapter as you read it, but that feeling of familiarity can be deceptively comforting. Using the Retrieve It opportunities, carve out study time for testing your knowledge.

Memory experts Elizabeth Bjork and Robert Bjork (2011, p. 63) offer the bottom line for how to improve your retention and your grades:

Spend less time on the input side and more time on the output side, such as summarizing what you have read from memory or getting together with friends and asking each other questions. Any activities that involve testing yourself—that is, activities that require you to retrieve or generate information, rather than just representing information to yourself—will make your learning both more durable and flexible.

Learning Objectives

Test Yourself by taking a moment to answer each of these Learning Objective Questions (repeated here from within the chapter). Research suggests that trying to answer these questions on your own will improve your long-term memory of the concepts (McDaniel et al., 2009).

Question

Question

Question

Question

Question

Question

Question

Question

Terms and Concepts to Remember

Test yourself on these terms.

Question

Experience the Testing Effect

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Test yourself repeatedly throughout your studies. This will not only help you figure out what you know and don’t know; the testing itself will help you learn and remember the information more effectively thanks to the testing effect.

Question 1.9

Question 1.10

Question 1.11

Question 1.12

Question 1.13

Question 1.14

Question 1.15

Question 1.16

Question 1.17

Question 1.18

Question 1.19

Question 1.20

Question 1.21

Question 1.22

Question 1.23

Use to create your personalized study plan, which will direct you to the resources that will help you most in .