Presentation on theme: "Chapter 1: Scientific Thinking"— Presentation transcript:

1 Chapter 1: Scientific Thinking

Your best pathway to understanding the world Lectures by Mark Manteuffel, St. Louis Community College



2 Section 1-1 Opener Already a scientist? It starts with curiosity.



3 Scientists Are curious Ask questions about how the world works

Seek answers Does the radiation released by cell phones cause brain tumors? Are anti-bacterial hand soaps better than regular soap? Do large doses of vitamin C reduce the likelihood of getting a cold? You are already a scientist. You may not have not have realized this yet, but it’s true. Because humans are curious, you have no doubt asked yourself or others questions about how the world works and wondered how you might find the answers. These are all important and serious questions. But you’ve probably also pondered some less weighty issues, too 



4 Science Not simply a body of knowledge or a list of facts to be remembered… …but rather an intellectual activity, encompassing observation, description, experimentation, and explanation of natural phenomena. To satisfy your curiosity and to explain seemingly unexplainable, mysterious, or magical things, curiosity and the desire to learn are not enough. Explaining how something works or why something happens requires methodical, objective, and rational observation and analysis that are not clouded with emotions or preconceptions about what is being studied and observed. Science is not simply a body of knowledge or a list of facts to be remembered, it is an intellectual activity, encompassing observation, description, experimentation, and explanation of natural phenomena. Put another way, science is a pathway by which we can come to discover and better understand the world around us. Later in this chapter, we explore specific ways in which we can most effectively use scientific thinking in our lives. But first let’s look at how our understanding of the world can be enhanced by asking the single question that underlies scientific thinking  (next slide).



5 “How do you know that is true?”

The single question that underlies scientific thinking Once you begin asking this question—of others and of yourself—you are on the road to a better state of understanding of the world.



6 …the importance of questioning the truth of many “scientific” claims you see on merchandise packages or read in the newspaper or on the internet. The following story about a popular and successful over-the-counter medicine shows the importance of questioning the truth of many “scientific” claims you see on merchandise packages or read in the newspaper or on the Internet. For more than ten years, a product called “Airborne” was marketed and sold to millions of customers. On the packaging and in advertisements, the makers asserted that Airborne tablets could ward off colds and boost your immune system (Figure 1-1 Some products claim to improve our health, but how do we know they work?). Not surprisingly, Airborne was a great success and generated more than one hundred million dollars in revenue and became one of the fastest selling health products ever. Then some consumers asked the makers of Airborne a reasonable question: How do you know that it wards off colds?



7 Learn exactly what it means to have scientific proof or evidence.

You don’t have to be at the mercy of cranks, charlatans, advertising, or slick packaging. Learn exactly what it means to have scientific proof or evidence. Learn what it means to think scientifically. Are you insulted by the CEO’s assumption about your intelligence? You should be. Did you or your parents (along with millions of other people) fall for Airborne’s false claims? Possibly. But here’s some more good news: you don’t have to be at the mercy of cranks, charlatans, advertising, or slick packaging that claim a product can ward off colds, make you lose 10 pounds in 7 days, make you healthier by cleansing your intestines, or increase or decrease the size of various body parts. You can learn to be skeptical and suspicious (in a good way) of such claims. You can learn exactly what it means to have scientific proof or evidence that something is absolutely true. And you can learn this by learning what it means to think scientifically.



8 Scientific Literacy how to think scientifically

how to use the knowledge we gain to make wise decisions increasingly important in our lives literacy in matters of biology is especially essential In this chapter, we explore how to think scientifically and how to use the knowledge we gain to make wise decisions. Although we generally restrict our focus to biology, scientific thinking can be applied to nearly every endeavor. In this chapter we use a wide range of examples, including some examples from beyond biology, as we learn how to think scientifically. Although the examples we use vary greatly, they all convey a message that is key to scientific thinking: it’s okay to be skeptical and you don’t need to take things on faith. Fortunately, learning to think scientifically is not difficult and it can be fun, particularly because it is so empowering. Scientific literacy, a general, fact-based understanding of the basics of biology and other sciences, is increasingly important in our lives and literacy in matters of biology is especially essential. As we see in the next section, issues hinging on biological ideas and processes are turning up in nearly every facet of our lives, from medicine to nutrition to relationships to politics and even to crime and justice.



9 Take-home message 1.1 Through its emphasis on objective observation, description, and experimentation, science is a pathway by which we can come to discover and better understand the world around us.



10 1.2 Biological literacy is essential in the modern world.

A brief glance at any newspaper will reveal… In the past, it was possible to get through life with little or no knowledge of science, but now scientific literacy has become a necessity. A brief glance at any newspaper will reveal just how many important health, social, medical, political, economic, and legal issues pivot on complex scientific data and theories. 



11 Biological issues—including global warming, fossil fuel use, stem cell research, and the proliferation of genetically modified foods—have also become important in political campaigns. And all around you, you will encounter products bearing too-good-to-be-true claims and technical-sounding language designed to lure you into purchasing them. Lack of biological literacy will put you at the mercy of “experts” who may try to confuse you or convince you of things in the interest of personal gain (Figure 1-2 In the news). Scientific thinking will help you to make wise decisions for yourself and for society.



12 Take-home message 1.2 Biological issues permeate all aspects of our lives. To make wise decisions, it is essential for individuals and societies to attain biological literacy.



13 1.3 The scientific method is a powerful approach to understanding the world.

If science proves some belief of Buddhism wrong, then Buddhism will have to change —Dalai Lama, 2005 It’s a brand new age and science, particularly biology, is everywhere. We are called upon more and more frequently to make decisions that hinge on our abilities to grasp biological information and to think scientifically.



14 To illustrate the value of scientific thinking in understanding the world, let’s look at what happens in its absence, by considering some unusual behaviors in the common laboratory rat. Rats can be trained without much difficulty to push a lever to receive a food pellet from a feeding mechanism (Figure 1-3 “In the absence of the scientific method…”). When the mechanism is altered so that there is a ten-second delay between the lever being pushed and the food pellet being dispensed, however, strange things start to happen. In one cage, the rat will push the lever and then, very methodically run and push its nose into one corner of the cage. Then it moves to another corner and again pushes its nose against the cage. It repeats this behavior at the third and fourth corners of the cage after which the rat stands in front of the feeder and the pellet is dispensed. Each time the rat pushes the lever it repeats the nose-in-the-corner sequence before moving to the food tray. In another cage, with the same ten-second delay, a rat may push the lever and then proceed to do three quick back flips in succession. It will then move to the food tray where the food pellet is dispensed when the ten seconds have elapsed. Like the first rat, the back-flip rat will repeat this exact behavior each time it pushes the lever.



15 Understanding How the World Works

Someone wonders about why something is the way it is and then decides to try to find out the answer. This process of examination and discovery is called the scientific method. As helpful and comforting as stories and superstitions may be (or as helpful as people think they are!), they are no substitute for really understanding how the world works: for really understanding, for example, that you are not sick because the gods are displeased with you but because the water you are drinking is contaminated, and that if the water can be purified, then you won’t get sick. This kind of understanding does not come all at once by some magical power; instead it begins when someone wonders about why something is the way it is and then decides to try to find out the answer. This process of examination and discovery is called the scientific method.



16 The Scientific Method Observe a phenomenon

Propose an explanation for it Test the proposed explanation through a series of experiments ↓ Accurate & valid, or… Revised or alternative explanations proposed The scientific method usually begins with someone observing a phenomenon and proposing an explanation for it. Next the proposed explanation is tested through a series of experiments. If the experiments reveal that the explanation is accurate, and if the experiments can be done by others with the same result, then the explanation is considered to be valid. If the experiments do not support the proposed explanation, then the explanation must be revised or alternative explanations that more closely reflect experimental results must be proposed. This process continues as better and more accurate explanations are found.



17 Scientific Thinking Is Empirical…

…based on experience and observations that are rational, testable, and repeatable. Scientific thinking can be distinguished from other alternative ways of acquiring knowledge about the world in that it is empirical. Empirical knowledge is based on experience and observations that are rational, testable, and repeatable. The empirical nature of the scientific approach makes it self-correcting: in the process of analyzing a topic, event or phenomenon with the scientific method, incorrect ideas are discarded in favor of more accurate explanations. In the next sections, we will look at how to put the scientific method into practice.



18 Once begun, though, it doesn’t necessarily continue linearly through the five steps until it is concluded (Figure 1-5 The scientific method: five basic steps and one flexible process). Sometimes observations made in the first step can lead to more than one hypothesis and several testable predictions and experiments. And the conclusions drawn from experiments often suggest new observations, refinements to hypotheses, and ultimately more and more precise conclusions. 18



19 What should you do when something you believe in turns out to be wrong?

This may be the most important feature of the scientific method: it tells us when we should change our minds. An especially important feature of the scientific method is that its steps are self-correcting. As we continue to make new observations, hypothesis about how the world works might change. If our observations do not support our current hypothesis, that hypothesis must be given up in favor of one that is not contradicted by any observations. This may be the most important feature of the scientific method: it tells us when we should change our minds. 19



20 1.5 Step 1: Make observations.

Look for interesting patterns or cause-and-effect relationships. It always begins with observations. At the first stage in the scientific method, we simply look for interesting patterns or cause-and-effect relationships. This is where a great deal of the creativity of science comes from. In the case of eyewitness testimony, we know now that new technologies have made it possible to assess whether tissue such as hair or blood from a crime scene came from a particular suspect. Armed with these tools, the Justice Department recently reviewed 28 criminal convictions that had been overturned by DNA evidence. They found that in most of the cases, the strongest evidence against the defendant had been eyewitness identification. The observation here is that many defendants who are later found innocent were initially convicted based on eyewitness testimony. 20



21 Does taking echinacea reduce the intensity or duration of the common cold?

Opportunities for other interesting observations are unlimited. Using the scientific method, we can (and will) answer all of the questions that follow. Many people have claimed that consuming extracts of the herb echinacea can reduce the intensity or duration of symptoms of the common cold. For this reason, it is widely used (Figure 1-7 The first step in science: making observations about the world). Returning to our fundamental question underlying the scientific method, we can ask: How do you know that is true? * Does taking echinacea reduce the intensity or duration of the common cold? 21



22 1.6 Step 2: Formulate a hypothesis.

A proposed explanation for observed phenomena Based on observations, we can develop a hypothesis (plural: hypotheses), a proposed explanation for observed phenomena. What hypotheses could we make about the eyewitness testimony observations described in the previous section? We could start with “Eyewitness testimony is always accurate.” We may need to modify our hypothesis later, but this is a good start. At this point, we can’t draw any conclusions. All we have done is to summarize some preliminary observations into a possible explanation for what we have observed. 22



23 Figure 1-8 Hypothesis: the proposed explanation for a phenomenon

23



24 To be most useful, a hypothesis must accomplish two things:

It must clearly establish mutually exclusive alternative explanations for a phenomenon. It must generate testable predictions. 1. It must clearly establish mutually exclusive alternative explanations for a phenomenon. That is, it must be clear that if the proposed explanation is not supported by evidence or further observations, a different hypothesis is a more likely explanation. 2. It must generate testable predictions (Fig. 1-9).  see next slide 24



25 The Null Hypothesis A negative statement that proposes that there is no relationship between two factors These hypotheses are equally valid but are easier to disprove. An alternative hypothesis It is impossible to prove a hypothesis is absolutely and permanently true. Often researchers will pose a hypothesis as a negative statement which proposes that there is no relationship between two factors, such as “Echinacea has no effect on the duration and severity of cold symptoms.” Or, “There is no difference in the coarseness or darkness of hair that has been shaved.” A hypothesis that states a lack of relationship between two factors is called a null hypothesis. These hypotheses are equally valid but are easier to disprove. This is because a single piece of evidence or a single new observation that contradicts a (null) hypothesis is sufficient to reject it and conclude that an alternative hypothesis is true or that it is highly probable that an alternative is true. In that case, once you have one piece of solid evidence that your null hypothesis is not true, you gain little by collecting further data. Conversely, it is impossible to prove a hypothesis is absolutely and permanently true: evidence or further observations that support a hypothesis are valuable but they do not rule out the possibility that some future evidence or observation might show that the hypothesis is not true. 25



26 Null and Alternative Hypotheses

Echinacea reduces the duration and severity of the symptoms of the common cold. Or as a null hypothesis: Echinacea has no effect on the duration or severity of the symptoms of the common cold. For our other observations, we could state our hypotheses two different ways as illustrated here and in the next few slides. 26



27 1.7 Step 3: Devise a testable prediction.

Suggest that under certain conditions we will make certain observations. This step of the scientific method really is part of the previous step. Formulating a hypothesis is important, but not all hypotheses are created equally. Some, in fact (such as our hypothesis about your dog loving you), are not helpful at all when it comes to helping us to better understand the world. For a hypothesis to be useful, it must generate a prediction. That is, it must suggest that under certain conditions we will make certain observations. Put another way, a good hypothesis helps us to make predictions about novel situations. That is a powerful feature of a good hypothesis: it guides us to knowledge about new situations. This is rather abstract. Let’s get more concrete with the four hypotheses presented in the previous section.  27



28 Devising a Testable Prediction from a Hypothesis

Keep in mind any one of several possible explanations could be true. Keep in mind that when you do not understand some aspect of the world, any one of several possible explanations could be true. 28



29 Devising a Testable Prediction from a Hypothesis

The goal is to: Propose a situation that will give a particular outcome if your hypothesis is true… …but that will give a different outcome if your hypothesis is not true. In devising a testable prediction from a hypothesis, the goal is to propose a situation that will give a particular outcome if your hypothesis is true, but that will give a different outcome if your hypothesis is not true. 29



30 Hypothesis: Echinacea reduces the duration and severity of the symptoms of the common cold.

Prediction: If echinacea reduces the duration and severity of the symptoms of the common cold, then individuals taking echinacea should get sick less frequently than those not taking it, and when they do get sick, their illness should not last as long. Figure 1-9 Devising a testable prediction. 30



31 1.8 Step 4: Conduct a critical experiment.

an experiment that makes it possible to decisively determine whether a particular hypothesis is correct Once we have formulated a hypothesis that generates a testable prediction, we conduct a critical experiment, an experiment that makes it possible to decisively determine whether a particular hypothesis is correct. There are many elements that are crucial in designing a critical experiment, and section 1-11 covers the details of this process. For now, it is important just to understand that with a critical experiment, if the hypothesis being tested is not true, we will make observations that compel us to reject that hypothesis. 31



32 Hypothesis: Echinacea reduces the duration and severity of the symptoms of the common cold.

The critical experiment for the echinacea hypothesis has been performed and it is about as close to a perfect experiment as possible. Researchers began with 437 people who volunteered to be exposed to viruses that cause the common cold. Exposure to the cold-causing viruses was a bit unpleasant: all of the volunteers had cold viruses (in a watery solution) dripped into their noses. Research subjects were then secluded in hotel rooms for five days, and doctors examined them for the presence of the cold virus in their nasal cavity and for any cold symptoms (Figure “When you need to know…”). 32



33 The subjects were randomly divided into four groups.



34 In two of the groups, each individual began taking a pill each day for a week prior to exposure to the cold virus. Those in one group received echinacea tablets while those in the other took a placebo, a pill that looked identical to the echinacea pill but contained no echinacea or other active ingredient. Neither the patient nor the doctor administering the pills knew what the pills contained.



35 In the other two groups, the individuals did not begin taking the pills until the day on which they were exposed to the cold virus. Again, one group got the echinacea pill and the other group got the placebo.



36 Take-home message 1.8 A critical experiment is one that makes it possible to decisively determine whether a particular hypothesis is correct. In the next section we’ll see how our hypotheses survive being confronted with the results of the critical experiments described above and how we can move toward drawing conclusions. 36



37 1.9 Step 5: Draw conclusions, make revisions.

Trial and error Once the results of the critical experiment are in, they are pulled apart, examined, and analyzed. Researchers look for patterns and relationships in the evidence they’ve gathered from their experiments, they draw conclusions and see if their findings and conclusions support their hypotheses. If an experimental result is not what you expected, that does not make it a “wrong answer.” Science includes a great deal of trial and error and if the conclusions do not support the hypothesis, then you must revise your hypothesis, which often spurs you to conduct more experiments. This step is a cornerstone of the scientific method because it demands that you must be open-minded and ready to change what you think. 37



38 The Role of Experiments

What is important is that we attempt to demonstrate that our initial hypothesis is not supported by the data. If it is not, we might then adjust our hypothesis. The results of the purse-snatching experiment were surprising. When the suspects were viewed together in a lineup, the observers/witnesses erroneously identified someone as the purse snatcher about a third of the time. When the suspects were viewed one at a time, the observers made a mistaken identification less than ten percent of the time. In this or any other experiment, it does not matter whether we can imagine a reason for the discrepancy between our hypothesis and our results. What is important is that we have demonstrated that our initial hypothesis—eyewitness testimony is always accurate—is not supported by the data. Our observations suggest that, at the very least, the accuracy of an eyewitness’ testimony depends on the method used to present suspects. Based on this result, we might then adjust our hypothesis to: “Eyewitness testimony is more accurate when suspects are presented to witnesses one at a time.” 38



39 Making Revisions Try to further refine a hypothesis.

Make new and more specific testable predictions. By making revisions, we can devise new and more specific testable predictions to try to further refine a hypothesis. In the case of eyewitness testimony, further investigation suggests that when suspects or pictures of suspects are placed side-by-side, witnesses compare them and tend to choose the suspect that most resembles the person they remember committing the crime. When viewed one at a time, suspects can’t be compared this way and witnesses are less likely to make misidentifications. 39



40 Does echinacea help prevent the common cold?

In the echinacea study, the results were definitive. Those who took the echinacea were just as likely to catch a cold, and, once they caught the cold, the symptoms lasted for the same amount of time. In short, echinacea had no effect at all. Several similar studies have been conducted, all of which have shown that echinacea does not have any beneficial effect. As one of the researchers commented afterward, “We’ve got to stop attributing any efficacy to echinacea.” Figure Drawing conclusions and making revisions. Although it seems clear that our initial hypothesis that echinacea prevents people from catching colds and reduces the severity and duration of cold symptoms is not correct, further experimentation might involve altering the amount of echinacea given to the research subjects or the length of time they took echinacea prior to exposure to the cold-causing viruses. Hypothesis: Echinacea reduces the duration and severity of the symptoms of the common cold. 40



41 1.10 When do hypotheses become theories?

Two distinct levels of understanding that scientists use in describing our knowledge about natural phenomena It’s an unfortunate source of confusion that to the general public the word “theory” is often used to refer to a hunch or a guess or speculation—that is, something we are not certain about—while to scientists, the word means nearly the opposite: a hypothesis of which they are most certain. To reduce misunderstandings, we examine two distinct levels of understanding that scientists use in describing our knowledge about natural phenomena. 41



42 Hypotheses and Theories

A hypothesis is a proposed explanation for a phenomenon. a good hypothesis leads to testable predictions. Hypotheses As we have seen, hypotheses are at the very heart of scientific thinking. A hypothesis is a proposed explanation for a phenomenon. A good hypothesis leads to testable predictions. Commonly when non-scientists use the word theory—as in, “I’ve got a theory about why there’s less traffic on Friday mornings than on Thursday mornings”—they actually mean that they have a hypothesis. 42



43 Hypotheses and Theories

A theory is a hypothesis for natural phenomena that is exceptionally well-supported by the data. a hypothesis that has withstood the test of time and is unlikely to be altered by any new evidence Theory A theory is an explanatory hypothesis for natural phenomena that is exceptionally well-supported by the empirical data. A theory can be thought of as a hypothesis that has withstood the test of time and is unlikely to be altered by any new evidence. 43



44 Theories vs. Hypotheses

Repeatedly tested Broader in scope Like a hypothesis, a theory is testable; but because it has been repeatedly tested and no observations or experimental results have contradicted it, a theory is viewed by the scientific community with nearly the same confidence as a fact. For this reason, it is inappropriate to describe something as “just a theory” as a way of asserting that it is not likely to be true. Theories in science also tend to be broader in scope than hypotheses. In biology, two of the most important theories (which we explore in more detail in Chapters 3 and 8) are: (1) cell theory: that all organisms are composed of cells and all cells come from preexisting cells, and (2) the theory of evolution by natural: that species can change over time and are all related to each other through common ancestry. 44



45 Take-home message 1.10 Scientific theories do not represent speculation or guesses about the natural world.



46 Take-home message 1.10 Theories are hypotheses that have been so strongly supported by empirical observation that the scientific community views them as very unlikely to be altered by new evidence.



47 1.11 Controlling variables makes experiments more powerful.

From our earlier discussion of critical experiments, you have a sense of how important it is to have a well-planned, well-designed experiment. Some experiments are just better than others when it comes to figuring out how the world works. At their most basic level, experiments help us to figure out the cause-and-effect relationship between two things. In the previous sections, for example, we hypothesized about the relationship between witnessing a crime and being able to identify the person who committed it, between taking echinacea and catching a cold and having it for a period of time, between water pollution and hermaphrodite fish, and between shaving and the subsequent coarseness and color of hair. In performing experiments, our goal is to figure out whether one thing influences another thing; if an experiment enables us to draw a correct conclusion about that cause-and-effect relationship, it is a good experiment. In our initial discussion of experiments, we just described what the experiment was without examining why the researchers chose to perform the experiment the way they did. In this section, we explore some of the ways to maximize an experiment’s power and find that with careful planning, it is possible to increase an experiment’s ability to discern causes and effects. 47



48 Elements Common to Most Experiments

1. Treatment any experimental condition applied to individuals 2. Experimental group a group of individuals who are exposed to a particular treatment 3. Control group a group of individuals who are treated identically to the experimental group with the one exception: they are not exposed to the treatment 4. Variables characteristics of your experimental system that are subject to change Here they all are. 48



49 Controlling Variables

the most important feature of a good experiment the attempt to minimize any differences between a control group and an experimental group other than the treatment itself When we speak of controlling variables—the most important feature of a good experiment—we are describing the attempt to minimize any differences between a control group and an experimental group other than the treatment itself. That way, any differences in the outcomes we observe between the groups are most likely due to the treatment. Let’s look at an example that illustrates the importance of considering all these elements when designing an experiment. 49



50 Stomach ulcers are erosions of the stomach lining that, due to the highly acidic condition of that part of the digestive tract, can be very painful. In the late 1950s, a doctor reported in the Journal of the American Medical Association that stomach ulcers could be effectively treated by having a patient swallow a balloon connected to some tubes that circulated a refrigerated fluid. He argued that by super-cooling the stomach, acid production was reduced and the ulcer relieved. He had convincing data to back up his claim: in all 24 of his patients who received the treatment, their condition improved. As a result, the treatment became widespread for many years (Figure No controls). 50



51 Is arthroscopic surgery for arthritis beneficial for the 300,000 people who have it each year?

How do we know? More recently, a well-controlled experiment demonstrated that arthroscopic knee surgery, a treatment for osteoarthritis done on more than 300,000 people each year, produced moderate benefits to the patient. But the study demonstrated even greater benefits to patients in a control group that was subjected not to the arthroscopic procedure but rather to “sham” surgery in which the surgeon made three superficial incisions in the knee, manipulated the knee a bit, and clanged the instruments around in the operating room. As a consequence of this study, many doctors have begun abandoning the use of arthroscopic surgery for the treatment of osteoarthritis—which once accounted for more than a billion dollars in surgical procedures each year. (This type of surgery is still useful for the treatment of some other knee problems, including the repair of ligament and cartilage damage.) 51



52 The Placebo Effect The phenomenon in which people respond favorably to any treatment The placebo effect highlights the need for comparison of treatment effects with an appropriate control group. A surprising result from both the gastric freezing studies and the arthroscopic surgery study was that they demonstrated the placebo effect, the frequently observed, poorly understood phenomenon in which people respond favorably to any treatment, regardless of whether it is as simple as a sugar pill or as unpleasant as having to swallow a balloon and have it inflated in their stomach. The placebo effect highlights the need for comparison of treatment effects with an appropriate control group. We want to know whether the treatment is actually responsible for any effect seen; if the control group receiving the placebo has an outcome like that of the experimental group, we can conclude that the treatment does not have an effect. 52



53 Clever Hans Another pitfall to be aware of in designing an experiment is to ensure that the person(s) conducting the experiment don’t influence the experiment’s outcome. An experimenter can often unwittingly influence the results of an experiment. For example, eyewitnesses to crimes more frequently identify the police’s suspect rather than other individuals in the lineup when the officer conducting the lineup knows which individual is the suspect. This phenomenon is seen in the story of a horse named Clever Hans. Hans was considered clever because his owner claimed that Hans could do remarkable intellectual feats, including multiplication and division. When given a problem, the horse would tap out the answer number with his foot. Controlled experiments, however, demonstrated that Hans was only able to solve problems when he could see the person asking the question and when that person knew the answer (Figure Math whiz or ordinary horse?). It turned out that the questioners revealed, unintentionally and through very subtle body language, the answers. 53



54 Experimental Designs Blind experimental design

The experimental subjects do not know which treatment (if any) they are receiving. Double-blind experimental design Neither the experimental subjects nor the experimenter knows which treatment the subject is receiving. The Clever Hans phenomenon highlights the benefits of instituting even greater controls when designing an experiment. In particular, it highlights the value of blind experimental design, in which the experimental subjects do not know which treatment (if any) they are receiving, and double-blind experimental design, in which neither the experimental subjects nor the experimenter knows which treatment the subject is receiving. 54



55 Hallmarks of an Extremely Well-designed Experiment

Blind/double-blind strategies Randomized The subjects are randomly assigned into experimental and control groups. Another hallmark of an extremely well-designed experiment is that it combines the blind/double-blind strategies we’ve just described in a randomized, controlled, double-blind study. In this context “randomized” refers to the fact that, like the echinacea study described above, the subjects are randomly assigned into experimental and control groups. In this way, researchers and subjects have no influence on the composition of the control and treatment groups. The use of randomized, controlled, double-blind experimental design can be thought of as an attempt to imagine all the possible ways that someone might criticize an experiment and to design the experiment so that the results cannot be explained by anything but the effect of the treatment. In this way, the experimenter’s results either support the hypothesis or it must be rejected. If multiple explanations can be offered for the observations and evidence from an experiment, then it has not succeeded as a critical experiment. 55



56 1.12 Repeatable experiments increase our confidence.

Can science be misleading? How can we know?



57 1.13 We’ve got to watch out for biases.

Can scientists be sexist? How would we know?



58 In 2001, the journal Behavioral Ecology changed its policy for reviewing manuscripts that were submitted for publication. Its new policy instituted a double-blind process, whereby neither the reviewers nor the authors’ identities were revealed. Previously, the policy had been a single-blind process in which reviewers’ identities were kept secret but the authors identities were known to the reviewers. In an analysis of papers published between 1997 and 2005, it turned out that there was a significant increase in the number of papers published in which the first author was a female after 2001 when the double-blind policy took effect (Figure Bias against female scientists?). Analysis of papers published in a similar journal that maintained the single-blind process during that period revealed no such increase. This study reveals that people, including scientists, may have biases—sometimes subconscious—that influence their behavior. It also serves as a reminder of the importance of proper controls in experiments. If knowing the sex of the author of a paper influences a reviewer’s decision as to whether it should be published, it is possible that researchers’ biases can creep in and influence their collection of data and analysis of results. 58



59 Take-home message 1.13 Biases can influence our behavior, including our collection and interpretation of data. With careful controls, it is possible to minimize such biases.



60 Section 1-4 Opener What can you believe? Reading labels is essential to evaluating products and the claims about them.



61 1.14 Statistics can help us to make decisions.

Earlier in this chapter, we saw that researchers repeatedly found, through experimentation, that megadoses of vitamin C do not reduce cancer risk. If you put yourself in the researchers’ shoes, you might wonder how you figure out that the vitamin C did not reduce cancer risk. Perhaps you had 100 patients in the group receiving megadoses of vitamin C: some of them developed cancer and some of them did not. And among the 100 patients in the group not receiving the megadoses some of the patients developed cancer and some did not. How do you decide whether the vitamin C actually had an effect? (go to next slide) 61



62 Statistics A set of analytical and mathematical tools designed to help researchers gain understanding from the data they gather. How do you decide whether the vitamin C actually had an effect? This knowledge comes from a branch of mathematics called statistics, a set of analytical and mathematical tools designed to help researchers gain understanding from the data they gather. To understand statistics, let’s start with a simple situation. 62



63 Larger numbers of participants are better than fewer if you want to draw general conclusions about natural phenomena. Suppose you measure the height of two people. One is a female who is 5'10" tall. The other is a male who is 5'6" tall. If these were your only two observations of human height, you might conclude that females are taller than males. But suppose you measure the heights of 100 females and 100 males chosen randomly from a population. Then you could can say “of the 100 men, the average man is 5'9.5“, and of the 100 women, the average woman is 5'4". Better still, the data can illuminate for you not only the average, but also some measure of how much variation there is from one individual to another. Statistical analysis can tell you not only that the average male in this study is 5’ 9.5” tall but that two-thirds of the men are between 5’6.5” tall (three inches less than the average) and 6’0.5” tall (three inches more than the average). You will often see this type of range printed as 5’9.5” ± 3”. Similarly, the data might show that the females in the study are 5’6” ± 3”, indicating that two-thirds of the females are between 5’3” and 5’9” tall. As we discussed earlier in the experiment design section and as this example shows, larger numbers of participants are better than fewer if you want to draw general conclusions about natural phenomena such as the height of men and women (Figure Drawing conclusions based on limited observations is risky). 63



64 Making Wise Decisions About Concrete Things

Does having access to a textbook help a student to perform better in a biology class? Students who had access to a textbook scored an average of 81% ± 8% on their exams… …while those who did not scored an average of 76% ± 7%. Using data to describe the characteristics of those participating in a study is useful, but often we want to know whether data support (or do not support) a hypothesis. If the scientific method is to be effective in helping us to understand the world, it must help us make wise decisions about concrete things. For example, suppose we want to know if having access to a textbook helps a student to perform better in a biology class. Statistics can help us to answer this question. After conducting a study, we may find that students who had access to a textbook scored an average of 81% ± 8% on their exams, whereas those who did not scored an average of 76% ± 7%. In this example, it is difficult to distinguish between the two possible conclusions: Possibility 1: Students having access to a textbook DO perform better in biology classes. In other words, this sampling of this class revealed a true relationship between the two variables: textbook access and class performance. Possibility 2: Students having access to a textbook DO NOT perform better in biology classes. The variation in scores in the two groups may be too large to make it possible to notice any effect of having access to a textbook. Instead, the difference in the average score for the two groups may mean that more of the high-performing students just happened to be put into the group given access to a textbook through random chance. 64



65 But what if the students with access to a textbook scored 95% ± 5%, while those without access scored only 60% ± 5%. In this case, we would be much more confident that there is a significant effect of having access to a textbook (Figure Drawing conclusions based on statistics), because even with the large variation in scores seen in each group, the averages are still very different from each other. Statistical methods help us to decide between these two possibilities and, importantly, to state how confident we are that one or the other is true. The greater the difference between two groups (95% versus 60% is a greater difference than 81% versus 76%) and the smaller the variation in each group (±5% in the 95% and 60% groups versus ± 8% and 7% in the 81% versus 76%), the more confident we are of the conclusion that there is a significant effect of the treatment (having access to a textbook in this case). In other words, in the case where the groups of students scored 95% or 60% depending on whether they had access to a textbook, it is possible that having a textbook does not actually improve performance and that this observed difference is just the result of chance. But this conclusion is very, very unlikely. 65



66 Statistics can also help us to identify relationships (or the lack of relationships) between variables. a positive correlation meaning that when one variable increases, so does the other Statistics can also help us to identify relationships (or the lack of relationships) between variables. For example, we might note that when there are more firefighters at a fire, the fire is larger and causes more damage. This is a positive correlation, meaning that when one variable (the number of firefighters) increases, so does the other (the severity of the fire). 66



67 “Correlation is not causation.”

Statistical analyses can help us to organize and summarize. Should we conclude that firefighters make fires worse? No. While correlations can reveal relationships between variables, they don’t tell us how the variables are related or whether change in one variable causes change in another. You may have heard or read the phrase “correlation is not causation,” which refers to this sort of situation. Before drawing any conclusions about more firefighters causing larger fires, we need to know the type of fire and its size when the firefighters arrive because those factors will significantly influence the ultimate amount of damage. To estimate the effect of the number of firefighters on the amount of damage, we would need to compare the amount of damage from fires of similar sizes that are fought by different numbers of firefighters. Ultimately, statistical analyses can help us to organize and summarize the observations that we make and evidence we gather in an experiment. These analyses can then help us to decide whether any differences we measure between experimental and control groups are likely to be the result of the treatment, and how confident we can be in that conclusion. 67



68 Take-home message 1.14 Because much variation exists in the world, statistics can help us evaluate whether differences between a treatment and control group can be attributed to the treatment rather than random chance.



69 1.15 Pseudoscience and misleading anecdotal evidence can obscure the truth.



70 Pseudoscience: individuals make scientific-sounding claims that are not supported by trustworthy, methodical scientific studies. Anecdotal observations: based on only one or a few observations, people conclude that there is or is not a link between two things. 70



71 “Four out of five dentists surveyed recommend sugarless gum for their patients who chew gum.”

“How do they know what they know?” Maybe the statement is factually true, but the general relationship it implies may not be. Beginning in the 1960s, for example, consumers encountered the assertion that “four out of five dentists surveyed recommend sugarless gum for their patients who chew gum.” If you ask yourself the question: “How do they know what they know?” and can’t answer it, you are looking at pseudoscience. Maybe the statement is factually true, but the general relationship it implies may not be. How many dentists were surveyed? If they surveyed only five dentists, then the statement may not represent the proportion of all dentists who would make such a recommendation. And how were the dentists sampled? Were they at a shareholders meeting for a sugarless gum company? What alternatives were given—perhaps gargling with a tooth-destroying acid? You just don’t know. That’s what makes it pseudoscience. 71



72 Anecdotal Observations

do not include a sufficiently large and representative set of observations of the world data are more reliable than anecdotes We are all familiar with anecdotal evidence. Striking stories or our own experiences can shape our views of cause and effect. We may find compelling parallels between suggestions made in horoscopes and events in our lives, or we may think that we have a lucky shirt, or we may be moved by a child whose cancer went into remission following treatment involving eating apricot seeds. Despite lacking a human face, data are more reliable than anecdotes, primarily because they can illustrate a broader range of observations, capturing the big picture. Anecdotal observations can seem harmless and can be emotionally powerful. But because they do not include a sufficiently large and representative set of observations of the world, they can lead people to draw erroneous conclusions, often with disastrous consequences. One important case of anecdotal evidence being used to draw general conclusions about a relationship between two things involves autism, a developmental disorder that impairs social interaction and communication, and the vaccination for measles, mumps, and rubella that is given to most children. We must be wary that we not generalize from anecdotal observations or let poorly designed studies obscure the truth. Figure Headline news. 72



73 Take-home message 1.15 Pseudoscience and anecdotal observations often lead people to believe that links between two phenomena exist, when in fact there are no such links.



74 1.16 There are limits to what science can do.

The scientific method will never prove or disprove the existence of God. Understand elegance? What is beauty? The scientific method is a framework that helps us make sense of what we see, hear, and read in our lives. Science and scientific thinking guide us in recognizing facts and help us in the interpretations of data, analyses of hypotheses, and drawing of conclusions. In doing so, scientific thinking reveals and illuminates explanations about how to think about various events and phenomena, and can help us to make decisions in diverse areas of our lives, not just “scientific” areas. There are, however, limits to what science can do. The scientific method will never prove or disprove the existence of God. Nor is it likely to help us understand the mathematical elegance of Fermat’s last theorem or the beauty of Shakespeare’s sonnets. 74



75 One of Several Approaches to the Acquisition of Knowledge

The scientific method is, above all, empirical. Value judgments and subjective information Moral statements and ethical problems As one of several approaches to the acquisition of knowledge, the scientific method is, above all, empirical. It differs from non-scientific approaches such as mathematics and logic, history, music, and the study of artistic expression in that it relies on measuring phenomena in some way. The generation of value judgments and other types of non-quantifiable, subjective information—such as religious assertions of faith—fall outside the realm of science. Despite all of the intellectual analyses the scientific method gives rise to and the objective conclusions it makes possible, it does not, for example, generate moral statements and it cannot give us insight into ethical problems. What “is” (i.e., what we observe in the natural world) is not necessarily what “ought” (i.e., what is morally right) to be. It may or may not be. Further, much of what is commonly considered to be science, such as the construction of new engineering marvels or the heroic surgical separation of conjoined twins, is not scientific at all. Rather, these are technical innovations and developments. While they frequently rely on sophisticated scientific research, they represent the application of research findings to varied fields, such as manufacturing and medicine, to solve problems. As we begin approaching the world from a more scientific perspective, we can gain important insights into the facts of life, yet must remain mindful of the limits to science. 75

