2.2 The Scientific Method

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

2-2 How do theories advance psychological science?

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

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.

hypothesis a testable prediction, often implied by a theory.

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 2.1 below). The results will either support our theory or lead us to revise or reject it.

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Figure 1.2: FIGURE 2.1 The scientific method A self-correcting process for asking questions and observing nature’s answers.

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.

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.

replication repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding can be reproduced.

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.

For more information about statistical methods that psychological scientists use in their work, see Appendix A, Statistical Reasoning in Everyday Life.

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.

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Question

sXbxZbUEH0TGTgv6jn1mV/hyvWQwA0neBhHAJxL+ENA=
ANSWER: 1. It organizes observed facts. 2. It implies hypotheses that offer testable predictions and, sometimes, practical applications. 3. It often stimulates further research.

Question

5lJhz0AMsg4Wn3EQrTrOHKiaeKCmJsBB81jkC6EoS9AgWvMO
ANSWER: When other investigators are able to replicate an experiment with the same (or better) results, scientists can confirm the result and become more confident of its reliability.

Description

2-3 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

“‘Well my dear,’ said Miss Marple, ‘human nature is very much the same everywhere, and of course, one has opportunities of observing it at closer quarters in a village’.”

Agatha Christie, The Tuesday Club Murders, 1933

case study a descriptive technique in which one individual or group is studied in depth in the hope of revealing universal principles.

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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.

image See LaunchPad's Video: Case Studies for a helpful tutorial animation.

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Freud and Little Hans Sigmund Freud’s case study of 5-year-old Hans’ extreme fear of horses led Freud to his theory of childhood sexuality. He conjectured that Hans felt unconscious desire for his mother, feared castration by his rival father, and then transferred this fear into his phobia about being bitten by a horse. Today’s psychological science discounts Freud’s theory of childhood sexuality but acknowledges that much of the human mind operates outside our conscious awareness.
Skye Hohmann/Alamy

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.

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Question

edkv3LG7rYcgLonA5i5SJJQfF5FMTBNCRlaAEK1e0JNusIrwW+bor79Q4Krf8IgS3tg8EwZek+dBlYQHnHgQ0tMnozdlfbKDPKf/RiC5bPuwVuNSVASqDa/f5YtDeOnXMOXiBTRw4E9tNp/Q
ANSWER: Case studies involve only one individual or group, so we can't know for sure whether the principles observed would apply to a larger population.

naturalistic observation a descriptive technique of observing and recording behavior in naturally occurring situations without trying to manipulate and control the situation.

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 2.2 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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Figure 1.3: FIGURE 2.2 Twitter message moods, by time and by day This illustrates how, without knowing anyone’s identity, big data enable researchers to study human behavior on a massive scale. It now is also possible to associate people’s moods with, for example, their locations or with the weather, and to study the spread of ideas through social networks. (Data from Golder & Macy, 2011.)

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image See LaunchPad's Video: Naturalistic Observation for a helpful tutorial animation.

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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An EAR for naturalistic observation Psychologists Matthias Mehl and James Pennebaker have used electronically activated recorders (EARs) to sample naturally occurring slices of daily life.
Courtesy of Matthias Mehl

Question

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ANSWER: The researchers were able to carefully observe and record naturally occurring behaviors outside the artificiality of the lab. However, outside the lab, they were not able to control for all the factors that may have influenced the everyday interactions they were recording.

survey a descriptive technique for obtaining the self-reported attitudes or behaviors of a particular group, usually by questioning a representative, random sample of the group.

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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.

population all those 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.)

random sample a sample that fairly represents a population because each member has an equal chance of inclusion.

With very large samples, estimates become quite reliable. E is estimated to represent 12.7 percent of the letters in written English. E, in fact, is 12.3 percent of the 925,141 letters in Melville’s Moby- Dick, 12.4 percent of the 586,747 letters in Dickens’ A Tale of Two Cities, and 12.1 percent of the 3,901,021 letters in 12 of Mark Twain’s works (Chance News, 1997).

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.

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Question

kL+PLKUHF2nX4TzURWjoZ0XSNHglfMnK9+PR4iF5pg+kJR/R5s0BILEVX3TzGJWQ3IuUm9m3dMy55vdp0HMKa13CuS4TdGj0
ANSWER: An unrepresentative sample is a group that does not represent the population being studied. Random sampling helps researchers form a representative sample, because each member of the population has an equal chance of being included.

Correlation

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2-4 What are positive and negative correlations, and why do they enable prediction but not cause-effect explanation?

correlation a measure of the extent to which two factors vary together, and thus of how well either factor predicts the other.

correlation coefficient a statistical index of the relationship between two things (from –1.00 to +1.00).

image See LaunchPad's Video: Correlational Studies for a helpful tutorial animation.

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.

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Indicate whether each association is a positive correlation or a negative correlation.

Question

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Question

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Question

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Question

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image For an animated tutorial on correlations, visit LaunchPad’s Concept Practice: Positive and Negative Correlations.

image

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 2.3 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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Figure 1.4: FIGURE 2.3 Three possible cause-effect relationships People low in self-esteem are more likely to report depression than are those high in self-esteem. One possible explanation of this negative correlation is that a bad self-image causes depressed feelings. But, as the diagram indicates, other cause-effect relationships are possible.

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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.

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Correlation need not mean causation.

Question

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ANSWER: It might. But in this case, as in many others, causation might work the other way around (more depressed people are more likely to hook up), or some third factor, such as lower impulsivity, might underlie both sexual restraint and psychological well-being.

Experimentation

2-5 What are the characteristics of experimentation that make it possible to isolate cause and effect?

Recall that in a well-done survey, random sampling is important. In an experiment, random assignment is equally important.

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).

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.

experimental group in an experiment, the group exposed to the treatment, that is, to one version of the independent variable.

control group in an experiment, the group not exposed to the treatment; contrasts with the experimental group and serves as a comparison for evaluating the effect of the treatment.

random assignment assigning participants to experimental and control groups by chance, thus minimizing preexisting differences between the -different groups.

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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Lane Oatey/Getty Images

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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.

image See LaunchPad's Video: Random Assignment for a helpful tutorial animation.

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.

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 a placebo. Commonly used in drug-evaluation studies.

And that is precisely how investigators evaluate new drug treatments and new methods of psychological therapy. 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.

placebo [pluh-SEE-bo; Latin for “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.

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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Question

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ANSWER: Research designed to prevent the placebo effect randomly assigns participants to an experimental group (receives the real treatment) or to a control group (receives a placebo), using a double-blind procedure (neither those who receive nor those who administer the treatment know who gets the placebo versus the actual treatment). A comparison of the results will demonstrate whether the real treatment produces better results than belief in that treatment.
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©The New Yorker Collection, 2007, P.C. Vey from cartoonbank.com. All Rights Reserved.

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.

independent variable in an experiment, the factor that is manipulated; the variable whose effect is being studied.

confounding variable a factor other than the factor being studied that might produce an effect.

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.

dependent variable in an experiment, the outcome that is measured; the variable that may change when the independent variable is manipulated.

image See two tutorial animations below: LaunchPad's Experiments and 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 2.4 for the British breast milk experiment’s design.)

image
Figure 1.5: FIGURE 2.4 Experimentation To discern causation, psychologists may randomly assign some participants to an experimental group, others to a control group. Measuring the dependent variable (intelligence score in later childhood) will determine the effect of the independent variable (type of milk).

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.

“[We must guard] against not just racial slurs, but … against the subtle impulse to call Johnny back for a job interview, but not Jamal.”

Barack Obama, Eulogy for Clementa Pinckney, June 26, 2015

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 2.1 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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Table 1.3: TABLE 2.1
Comparing Research Methods
Research Method Basic Purpose How Conducted What Is Manipulated Weaknesses
Descriptive To observe and record behavior Do case studies, naturalistic observations, or surveys Nothing No control of variables; single cases may be misleading
Correlational To detect naturally occurring relationships; to assess how well one variable predicts another Collect data on two or more variables; no manipulation Nothing Cannot specify cause and effect
Experimental To explore cause and effect Manipulate one or more factors; use random assignment The independent variable(s) Sometimes not feasible; results may not generalize to other contexts; not ethical to manipulate certain variables

THINKING CRITICALLY ABOUT

Research Design: How Would You Know?

Throughout this book, you will read about amazing psychological science discoveries. But how do we know fact from fiction? How do psychological scientists choose research methods and design their studies in ways that provide meaningful results? Understanding how research is done—how testable questions are developed and studied—is key to appreciating all of psychology.

In psychological research, no questions are off limits, except untestable ones. Does free will exist? Are people born evil? Is there an afterlife? Psychologists can’t test those questions, but they can test whether free will beliefs, aggressive personalities, and a belief in life after death influence how people think, feel, and act (Dechesne et al., 2003; Shariff et al., 2014; Webster et al., 2014).

To help you build your understanding, and your scientific literacy skills, we created IMMERSIVE LEARNING research activities in LaunchPad. In these How Would You Know activities, you get to play the role of the researcher, making choices about the best ways to test interesting questions, such as How Would You Know If Having Children Relates to Being Happier?, How Would You Know If a Cup of Coffee Can Warm Up Relationships?, and How Would You Know If People Can Learn to Reduce Anxiety?

Having chosen their question, psychologists then select the most appropriate research design—experimental, correlational, case study, naturalistic observation, twin study, longitudinal, or cross-sectional—and determine how to set it up most effectively. They consider how much money and time are available, ethical issues, and other limitations. For example, it wouldn’t be ethical for a researcher studying child development to use the experimental method and randomly assign children to loving versus punishing homes.

Next, psychological scientists decide how to measure the behavior or mental process being studied. For example, consider the researchers mentioned earlier in this box, who tested whether aggressive personalities affect how people act. They measured aggression by determining participants’ willingness to blast a stranger with intense noise.

Researchers want to have confidence in their findings, so they carefully consider confounding variables—factors other than those being studied that may affect their interpretation of results.

Psychological research is a fun and creative adventure. The new Immersive Learning: How Would You Know? activities invite you to join the scientific journey to uncover new knowledge. We will both [DM and ND] encourage you via videos as you DESIGN each of your studies, MEASURE target behaviors, INTERPRET your results, and learn more about the fascinating process of scientific discovery along the way!

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image To review and test your understanding of experimental methods and concepts, visit LaunchPad’s Concept Practice: The Language of Experiments, and the interactive PsychSim 6: Understanding Psychological Research. For a 9.5-minute video synopsis of psychology’s scientific research strategies, click here to visit LaunchPad’s Video: Research Methods.

RETRIEVE IT

Question

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ANSWER: The independent variable, which the researchers manipulated, was the set of ethnically distinct names. The dependent variable, which they measured, was the positive response rate.

Question

By using random assignment, researchers are able to control for 0ZRuWpHgrpTl7/lAu3tnJuJ8b+HP15BCP1sxqg== , which are other factors besides the independent variable(s) that may influence research results.

Match the term on the left with the description on the right.

Question

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Question

Z+Re+0bl9ic3uewM1yid6J1EjdISbNZhZqZqp8nOJr4yhqRdUNUOU3rxE2fWOYL/yAxHvXFTv7CJH0y9d8pWAp7EWDlDOrg4dCjk9mJSJ2iXL3K8inbj8WVsI1y1askSEFNw3tIHC29+ib5p1tGfPhsis+DXGaU1E0bNgFOjFecfWgF6Q6ly6flLcWKRniQ9JoH/uqCT5STkAB+XSuTbp0NkcZ4eiP4SpVoa/fwbF369GsMVo2MwpibjfxrOtxTGhlKjXg==
ANSWER: We learn more about the drug's effectiveness when we can compare the results of those who took the drug (the experimental group) with the results of those who did not (the control group). If we gave the drug to all 1000 participants, we would have no way of knowing whether the drug is serving as a placebo or is actually medically effective.

Predicting Real Behavior

2-6 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 principlesnot the specific findingsthat 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.