Chapter 1. Chapter 1: Process of Science

1.1 Introduction

Welcome to the Interactive Study Guide for Chapter 1: Process of Science! This Study Guide will help you master your understanding of the chapter's Driving Questions, using interactive Infographics and activities, as well as targeted assessment questions. Click "Next" to get started, or select a Driving Question from the drop-down menu to the right.

DRIVING QUESTIONS

• How is the scientific method used to test hypotheses?
• What factors influence the strength of scientific studies and whether the results of any given study are applicable to a particular population?
• How can you evaluate the evidence in media reports of scientific studies?
• How does the scientific method apply in clinical trials designed to investigate important issues in human health?

1.2 Driving Question 1

Why should you care?

When we understand how science works and how scientific evidence is obtained, interpreted and refined, we can analytically and critically evaluate the findings we read about in the media. Then we can make good, evidence-based decisions about our lifestyle choices rather than following the latest fads.

What should you know?

To fully answer this Driving Question, you should be able to:

1. Describe and discuss the process of science from initial observations to publishable results.
2. Compare and contrast the conclusions generated by rigorous scientific study and those generated anecdotally.

1.3 Driving Question 2

Why should you care?

The strength of a scientific study’s conclusions depends on the quality of the study’s design. Controlled experiments are one of the most powerful tools scientists use to test hypotheses. Understanding the characteristics of a good controlled experiment helps us evaluate the conclusions we read about in media reports. Sample size is also a critical component of good research design. Typically, conclusions from studies with small sample sizes are only weakly supported. When you read media reports, one of the first things you should look for is sample size; if it is small or if it is not reported, you should remain skeptical about the reported conclusions.

What should you know?

To fully answer this Driving Question, you should be able to:

1. Compare and contrast the control and experimental groups of a controlled experiment.
2. Describe the design of a controlled experiment.
3. Illustrate and discuss the significance of sample size on the strength of conclusions drawn from scientific studies.

Infographic Focus

The infographics most pertinent to the Driving Question are 1.3, 1.4, and 1.7.

Illustrate and discuss the significance of sample size on the strength of conclusions drawn from scientific studies.

20.

Examine the two graphs from Infographic 1.4. For each, write a one-sentence statement of what the graph shows about the relationship between milligrams of caffeine per day and score on the memory test.

For the first graph, increased consumption of caffeine slightly increases performance on memory tests. For the second graph, increased consumption of caffeine greatly increases performance on memory tests.

21.

The following table contains hypothetical data from a study of the effects of caffeine consumption on a test of short-term memory in college students.

Participant	Caffeine (mg)	Test Score (points out of 100)
1	0	20
2	50	30
3	100	60
4	150	100
5	200	100
6	0	55
7	50	70
8	100	45
9	150	50
10	200	40
11	0	60
12	50	40
13	100	35
14	150	40
15	200	45

Table

Graph the results for the first five participants and write a one-sentence statement explaining what it shows about the relationship between caffeine consumption and short-term memory.

Increased consumption of caffeine greatly enhanced performance on a short-term memory test.

22.

On the same graph, show the results for the remaining participants and write a one-sentence statement explaining what it shows about the relationship between caffeine consumption and short-term memory.

Increased consumption of caffeine slightly enhanced performance on a short-term memory test.

23.

Explain why your conclusions differ in terms of individual participants.

In the first data set and graph, the more caffeine individuals had, the better they performed on the short-term memory test. In the second data set and graph, the correlation between increased caffeine consumption and memory test scores did not remain. Some individuals in this group had a high level of caffeine but did not perform well on the memory test (for example, individual #13).

24.

Explain why the conclusions based on the larger sample (15) are more reliable than those based on the smaller sample (5).

The larger the sample, the more likely you are to see all of the possible outcomes of your experiment. If you used only five people in your study on caffeine and short-term memory, you would have concluded that there was a strong effect of the caffeine. Based on the results from the larger group of 15, this finding would have been inaccurate.

25.

Now look at the statements you wrote about the graphs in Infographic 1.4. Which of the two sets of data is more reliable? Why?

The larger the sample size, the more likely you are to see all of the possible outcomes of your experiment. If you only used 5 people in your study on caffeine and short-term memory, you would have concluded that there was a strong effect of the caffeine, which, based on the results from the larger group of 15, would have been inaccurate.

1.4 Driving Question 3

Why should you care?

Most of us are not health care professionals. Lacking the knowledge and skills to read, understand, and synthesize all of the scientific literature about human health, we must rely instead on media reports to stay informed of the latest findings and trends. We cannot, however, take those reports at face value. We need a proper understanding of the process of science to critically evaluate what we read and to use what we read to make good decisions about our own lifestyle choices. Understanding how and why important details may be missing from media reports is the final piece to helping you become a critical and analytical consumer of scientific news.

What should you know?

To fully answer this Driving Question, you should be able to:

1. Compare and contrast the everyday and scientific meanings of the word “theory.”
2. Explain why a correlation in a scientific study does not necessarily indicate a cause-and-effect relationship.
3. Explain why media headlines may not accurately convey the results of scientific studies.
4. List and describe the questions a skeptical consumer should ask about a media report before accepting the reported conclusions at face value.

Infographic Focus

The infographics most pertinent to the Driving Question are 1.2, 1.3, 1.4, 1.5, 1.7, and 1.8.

Explain why a correlation in a scientific study does not necessarily indicate a cause-and-effect relationship.

32.

Based on the epidemiological study mentioned in the textbook, does caffeine cause a reduction in the risk of developing Parkinson disease? If not, how do you explain the pattern shown on the graph in Infographic 1.7?

There is no strong evidence that caffeine causes a reduction in the risk of developing Parkinson disease. The evidence presented in Infographic 1.7 is flawed in many ways: the experimental group studied is Japanese-American men and results from this group may not match results that would be obtained from a different population, say African-American women. There is no control group, so an absolute causation statement of caffeine reducing the risk of Parkinson disease cannot be made. (Rather, there is only a correlation between more caffeine intake and less risk of Parkinson.) The other variables in the group, such as stress, whether or not they had children, and location of home, are not controlled for, so it is possible that one of these factors may also be playing a role in the lowered risk of Parkinson disease.

33.

What principle about correlation and cause-and-effect relationships does this example illustrate?

A correlation is simply a relationship between two observations (like increased caffeine use and lowered Parkinson risk), while a cause-and-effect relationship states that one thing is responsible for the other (like caffeine consumption improves memory in adults over the age of 65). A correlation between two things does not imply that one thing is a result of the other; rather it just says that there is some relationship between the two.

1.5 Driving Question 4

Why should you care?

When you understand the elements of good scientific studies and some of the cautions that you must exercise when interpreting their results, you are better prepared to take information transmitted through popular media and decide, as an educated consumer, how it affects you.

What should you know?

To fully answer this Driving Question, you should be able to:

1. Use all of the information learned in this chapter to assess the claims and evidence reported in clinical trials.

Infographic Focus

All of the infographics are pertinent to the Driving Question.

Test Your Vocabulary

Choose the correct term for each of the following definitions:

Term	Definition
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	Subject to support or rejection (of a hypothesis) according to carefully designed experiments or observational studies.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	An informal observation that has not been systematically tested.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	A tentative explanation for a scientific observation or question.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The measured result of an experiment analyzed in both the experimental and control groups.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The group in an experiment that undergoes the experimental intervention or manipulation.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	A fake treatment given to control groups to mimic the experience of the experimental groups.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	A measure of confidence that the results obtained are “real” and not due to chance.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	A consistent relationship between two variables.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The study of patterns of disease in populations, including risk factors.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The number of experimental subjects or the number of times an experiment is repeated In human studies, sample size is the number of participants.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	A process in which independent scientists read scientific studies before they are published to ensure that the authors have appropriately designed and interpreted the study.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	carefully designed test, the results of which will either support or rule out a hypothesis.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	A controlled medical experiment in which subjects are randomly chosen to receive either an experimental treatment or a standard treatment (or placebo).
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	explanation of the natural world that is supported by a large body of evidence and has never been disproved.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The group in an experiment that undergoes no experimental intervention or manipulation.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	(A hypothesis) demonstrably ruled out by data showing that the hypothesis does not explain the observation.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The variable, or factor, being deliberately changed in the experimental group.
--------scienceanecdotal evidencepeer reviewhypothesistestablefalsifiableexperimentexperimental groupcontrol groupplaceboindependent variabledependent variablesample sizestatistical significancescientific theorycorrelationrandomized clinical trialepidemiology	The process of using observations and experiments to draw conclusions based on evidence.

Table

999

Try again.

Correct.

Incorrect.

39.

Read the summary provided as a popular media report of the peer-reviewed article “Insufficient Sleep Undermines Dietary Efforts to Reduce Adiposity” by Nedeltcheva et al. (Annals of Internal Medicine 153:435-441, 5 October 2010) and answer the questions. Note that some questions address the scientific study itself while others address the way in which the study is reported. Both are important!

Excerpt from the Media Report

Sleeping Helps You Lose!

Researchers from the University of Chicago and the University of Wisconsin, Madison, recently reported new findings on the relationship between sleep and weight loss. In a randomized clinical trial, subjects getting 5.5 hours of sleep over a 2-week period lost the same amount of weight as their counterparts getting 8.5 hours of sleep. But subjects on the low-sleep regimen lost significantly more lean muscle and significantly less body fat than did subjects on the long-sleep regimen. Therefore, the more sleep you get, the more body fat you will lose!

Excerpt from the Research Paper

The study examined sleep and weight loss in 10 overweight, non-smoking individuals (3 women and 7 men). Subjects were randomly assigned to two treatments: 8.5 hours of sleep or 5.5 hours of sleep. All subjects were given the same moderately restricted diet, moderate exercise regimen and studied for 2 weeks in a sleep laboratory. Investigators measured fat loss and fat-free body mass as well as several physiological variables related to how the body uses energy. Based on the results, insufficient sleep undermines dietary efforts to reduce body fat.

What type of study is this? Diagram the study, being sure to identify (a) the question being asked, (b) control group and experimental group, (c) the independent variable, (d) the dependent variable and how it was measured, and (e) the conclusions the authors of both articles reached. (Hint: Use the scheme illustrated in Infographic 1.3.)

(a)Question: Does sleep affect weight loss?
(b)Control Group:
Moderately restricted diet
Moderate exercise regimen
2 weeks in Sleep Lab
Weight Measurement: percent body fat vs. body mass
Weight Result: lost more lean muscle and less fat
Experimental Group:
Moderately restricted diet
Moderate exercise regimen
2 weeks in Sleep Lab
Weight Measurement: percent body fat vs. body mass
Weight Result: lost more fat and less lean muscle
(c)Independent variable: length of sleep
(d)Dependent variable: weight loss through body fat and lean muscle reduction
Measurement: weight, percent body fat, and total body mass
(e)Conclusion of media report author: More sleep will make you lose more body fat.
Conclusion of research paper author: Sleeping 5.5 hours per night will cause you to lose less body fat and more lean muscle when reducing calorie intake than people getting 8.5 hours of sleep.

40.

What is the sample size of the study? Does the size of the sample influence your confidence in the results of the study? Explain. Do any of the other features of the study design reduce your confidence in the results? Explain.

The sample size of the study was 10 individuals, three women and seven men. This sample is very small and disproportionate in terms of gender. Nowhere in the description does it say that all subjects had the same starting percentage of body fat versus body mass or the same metabolic rate. The term “overweight” is also used to describe all participants, although the parameters of overweight are never defined. Sleep is also only measured in hours; the study says nothing about the quality of sleep. For example, one participant in the 8.5 hour group could wake up every 2 hours, while one participant in the 5.5 hour group could sleep soundly for the whole period. The stress of staying and sleeping in a sleep lab for 2 weeks would also affect people’s stress level and metabolism differently, so it is hard to say that it was only the length of sleep that mattered in terms of fat loss.
I would not have much confidence in this study based on these design shortfalls.

41.

Does the study report a correlation, a causal relationship, or both? If it’s a correlation and not a causal relationship, offer at least one explanation for the correlation other than the effects of sleep itself.

At best, the research paper offers a correlation. There is a possibility that one group contained only male participants (five in a group and seven participants were male of 10 total). If this group was given the 8.5-hour sleep treatment, their resting metabolism while they are sleeping may be higher than the other group’s, and when added to the extended sleep time, this combination may result in more fat loss.

42.

Does the media report include sufficient detail about the study for you to make an informed decision about the strength of the author’s conclusion? If not, which details are missing and why are they important?

No, the media report does not include sufficient detail about the study to support the author’s conclusion. This report does not mention the sample size, the traits (e.g., gender, ethnicity, physical shape) of the participants and shows no evidence to claim that more sleep (over 8.5 hours) would increase the amount of body fat lost. All of these details are important for the reader to assess the validity of the claims and the data being presented.

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