research power point and outline on  the state of Ketosis / Ketogenic diet. how does the topic tie into biology and the chapters in the book linked in the directions doc.

Biology 100 Project

KETOGENIC DIET / STATE OF KETOSIS

Project requirements Create a PowerPoint presentation on a topic related to the field/study of Biology. Your presentation must be 10-15 minutes in length and must answer the following questions: (no more than 10-15 slides)

1) What is your subject and why is it significant in the study of biology? 2) How does this topic relate to other topics we have discussed in class?

2) http://www.macmillanhighered.com/launchpad/phelan3e/8033058/Home#/ebook/ (use this text book link for your references and to review the chapters we have discussed.) chapters 1, 2, 5, &7. You may also use other chapters in this book that have not been discussed but please be sure to explain your information in detail in your outline and notes section of your powerpoint. 3) What is still unknown about your topic? 4) How does your topic relate to the world in general? (Economics, scientific research, people, etc?) 5) How is your topic historically significant? Who were the “major players” in developing the theories and methods behind your topic? (For instance, if you choose genetics, you may want to discuss Watson and Crick, Rosalind Franklin, etc.) 6) Where is the current research in your topic headed? Why is there an interest in your topic among scientists? 7) What other significant advances or points can you add concerning your topic?

3) Add pictures and one short video into your PowerPoint.

Students are to work in small groups. Each person is responsible for their portion of the presentation. Along with their slide presentations, students must submit a bibliography of sources, an outline of the presentation, and 5 test questions. This is due approximately one week before the scheduled presentation. An outline consists of the major topics discussed, as well as a brief description of each. The outline is a GUIDE for the presentation, not the “meat” of the project.

· ***A Note about PowerPoint Presentations:

· All slides should have the same or similar backgrounds.

· Follow the 7-7-7 rule- No more than seven words to a line, seven lines to a slide and spend no more than seven minutes on any one slide.

· Do not clutter your slides with words. Slides are meant to punctuate your lecture, not carry it for you.

Follow up After each presentation, questions are asked concerning each topic, and any points that were missed in the presentation are covered by the instructor.

Homework Compile a list of resources and create an outline for your presentation.

Evaluation Students are evaluated using a rubric provided by the instructor.

Chapter 1: Scientific Thinking

Your best pathway to understanding the world

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Welcome to the lecture corresponding to chapter 1: scientific thinking.

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Learning Goals

Describe what science is.

Describe the scientific method.

Describe key aspects of well-designed experiments.

Describe how the scientific method can be used to help make wise decisions.

Describe the major themes in biology.

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In this chapter we will be covering the following learning objectives <please read the learning goals>

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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?

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What is a scientist? Well, 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. And if you really put your mind to the task, you will start to find questions all around whose answers you might like to know (and, like those above, whose answers you will learn as you read this book).

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Science

Not simply a body of knowledge or a list of facts to be remembered

It is intellectual activity, encompassing observation, description, experimentation, and explanation of natural phenomena.

The single question that underlies scientific thinking: How do you know that is true?

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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: How do you know it is true? 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.

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The truth of “scientific claims”

You do not 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.

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Read some examples of false claims of the effects of certain products in the book (Airborne, health benefits of Dannon yogurt etc.)

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. Scientific thinking is an important and productive element in the study of a wide variety of topics: it can help you understand economics, psychology, history, and many other subjects.

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Biology: The study of living things

Its more important questions:

What is the chemical and physical basis for life and its maintenance?

How do organisms use genetic information to build themselves and to reproduce?

What are the diverse forms that life on earth takes and how has that diversity arisen?

How do organisms interact with each other and with their environment?

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Our focus in this book is biology, the study of living things.

Taking a scientific approach, we will investigate the facts and ideas in biology that are already known and will study the process by which we come to learn new things.

As we move through the four parts of the book, we explore the most important questions in biology <please read the questions>

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Scientific and Biological Literacy

The ability to:

use the process of scientific inquiry to think creatively about real-world issues

communicate those thoughts to others

integrate those thoughts into your decision-making

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Biological literacy doesn’t just involve the big issues facing society or abstract ideas.

It also matters to you personally.

Should you take aspirin when you have a fever?

Are you doing something wrong if you try to lose weight and, after a period of initial success, you find your rate of weight loss diminishing?

Is it a good idea to consume moderate amounts of alcohol?

In summary, scientific literacy means <please read the slide>

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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

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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.

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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.

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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.

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1.4 The Scientific Method

Scientific Thinking Is Empirical = based on experience and observations that are rational, testable, and repeatable.

Observe a phenomenon

Propose an explanation for it

Test the proposed explanation through a series of experiments

↓

Accurate and valid

or…

Revised or alternative explanations proposed

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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.

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The basic steps in the scientific method are:

Step 1: Make observations.

Step 2: Formulate a hypothesis.

Step 3: Devise a testable prediction.

Step 4: Conduct a critical experiment.

Step 5: Draw conclusions and make revisions.

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The slide shows the basic steps in the scientific method. “Scientific method” – this term sounds like a rigid process to follow, much like following a recipe.

In practice, however, the scientific method is not one single method that is always rigidly followed from start to finish.

Rather, it is an adaptable process that includes many different methods.

This flexibility makes the scientific method a more powerful process that can be used to explore a wide variety of thoughts, events or phenomena not only in science, but in other areas as well.

Once begun, though, it doesn’t necessarily continue linearly through the five steps until it is concluded. 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.

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The Scientific Method is self-correcting

Something you believe in may be wrong.

This may be the most important feature of the scientific method:

it tells us when we should change our minds.

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An especially important feature of the scientific method is that its steps are self-correcting.

As we continue to make new observations, hypotheses 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.

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1.5 Step 1: Make observations.

Look for interesting patterns or cause-and-effect relationships: ex.

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

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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.

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. 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?

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1.6 Step 2: Formulate a hypothesis.

Hypothesis: A proposed explanation for observed phenomena

It should be testable & must clearly establish mutually exclusive alternative explanations for a phenomenon

Be aware that in common language a hypothesis is called a “theory.”

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Based on observations, we can develop a hypothesis (plural: hypotheses), a proposed explanation for observed phenomena.

In the equinacea example, we can hypothesize that “it reduces the duration and severity of the common cold.”

A hypothesis should: 1. 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. generate testable predictions

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1.7 Step 3: Devise a testable prediction.

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.

Keep in mind any one of several possible explanations could be true.

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

This is rather abstract.

Let’s get more concrete with the four hypotheses presented in the previous section. 

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Devising Testable Predictions

Researchers often pose a hypothesis as a negative statement, proposing that there is no relationship between two factors=> null hypothesis (easier to disprove): Echinacea has no effect on the duration and severity of cold symptoms.”

Alternative hypothesis

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A hypothesis that can never be shown, by some observation, to be untrue is not a useful hypothesis.

Often researchers will pose a hypothesis as a negative statement that proposes that there is no relationship between two factors, such as “Echinacea has no effect on the duration and severity of cold symptoms.”

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.

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

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So our Hypothesis is that Echinacea reduces the duration and severity of the symptoms of the common cold.

And our Prediction is that 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.

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1.8 Step 4: Conduct a critical experiment.

Equinacea experiment: 437 volunteers exposed to the common cold virus, 4 groups:

Taking pill before exposure to virus:

Group 1 taking placebo (identical pill no equinacea)

Group 2 taking echinacea pill

Taking pill after exposure

Group 3 Placebo

Group 4 equinacea

Neither the patient nor the doctor administering the pills knew what the pills contained.

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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.

(please read the slide)

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.

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1.9 Step 5: Draw conclusions, make revisions.

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

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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.

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 1-13 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.

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Take-home message 1.9

Experimental test results can be used to revise hypotheses and explain the observable world more accurately.

Scientific thinking helps us to understand when we should change our minds.

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The results in all of these studies show that after the results of a critical experiment have been gathered and interpreted, it is important not just to evaluate the initial hypothesis but also to consider any necessary revisions or refinements to it.

This revision is an important step; by revising a hypothesis, based on the results of experimental tests, we can explain the observable world with greater and greater accuracy.

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1.10 Hypotheses and Theories

A hypothesis is a proposed explanation for a phenomenon: a good hypothesis leads to testable predictions.

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 (cell theory, evolution)

Theory: Repeatedly tested, broader in scope

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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.

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.

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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

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First, let’s describe some elements common to most experiments. These include:

Treatment – this is any experimental condition applied to individuals. It might be a dosage of echinacea given to an individual.

Experimental group – a group of individuals who are exposed to a particular treatment. This would be, for example, the individuals given echinacea rather than placebo in the experiment described above.

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. This would be, for example, the individuals given placebo rather than echinacea.

Variables – these are characteristics of your experimental system that are subject to change. They might be, for example, the amount of echinacea a person is given, or a measure of the coarseness of an individual’s hair.

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1.11 Controlling variables makes experiments more powerful.

In experiments, it is essential to hold constant all those variables in which we are not interested.

Control and experimental groups should vary only with respect to the treatment of interest.

Differences in them can then be attributed to the treatment.

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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.

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Factors to consider

Placebo effect: people will respond to “any treatment,” therefore importance of control groups

“Clever Hans” phenomenon: influence of the person conducting the experiment, therefore importance of blind and double blind designs

Effect of researchers and subjects, therefore importance of randomized studies

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What is the placebo effect? Sometimes people will respond to any treatment, just to the fact that they are receiving a treatment. Therefore the importance of control groups, groups that are as similar as possible to the experimental group and receive the same treatment except the actual variable tested. So for example patients will receive a pill that does not contain the drug being tested. There is also a subconscious bias of the person conducting the experiment, so it is recommended to have blind (the test subject does not know which group he belongs) or even better double blind (where neither the tester nor the experimenter knows who is in which group) tests. Which subjects go to the control and which go to the experimental group should be randomized to avoid subconscious bias (for example putting patients who are healthier to the experimental group).

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1.12-13: Repetition & bias

Experiments and their outcomes must be reproducible and repeatable for their conclusions to be valid and widely accepted.

Biases can influence our behavior, including our collection and interpretation of data.

With careful controls, it is possible to minimize such biases.

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A powerful way to demonstrate that differences observed between a treatment group and a control group truly reflect the effect of the treatment is to conduct the experiment over and over again.

Even better is to have other individuals repeat the experiment and get the same results.

Researchers describe this desired characteristic of an experiment by saying that an experiment must be reproducible and repeatable. It also serves as a reminder of the importance of proper controls in experiments.

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1.14 Visual displays of data can help us understand and explain phenomena.

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Many different graphic types

Common elements:

X axis

Y axis

Variables

Data points

Title

Can be manipulated and become misleading

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Using points and lines and symbols and a variety of other graphic elements to display measured quantities is a powerful tool commonly used throughout the sciences. Such visual displays of data can serve a range of purposes, which relate to both the presentation of and the exploration of the data.

Visual displays of data typically have one feature in common: they condense large amounts of information into a more easily digested form. Visual displays of data generally have a few common elements. Most have a title, for example, which usually appears at the top and describes the content of the display. Bar graphs and line graphs include axes, usually a horizontal axis, also called the x-axis, and a vertical axis, called the y-axis. Each axis has a scale, generally labeled with some gradations, indicating one dimension by which the data can be described.

The x-axis of a line graph, for example, might describe the number of hours a student spends studying for a class, in which case it would be labeled “Time spent studying each day (hrs),” while the y-axis might be labeled “Performance on midterm exams (%).”

A line or curve may be used to connect data points or to illustrate a relationship between the two variables.

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Variables

Independent Variables

some measurable entity that is available at the start of a process and whose value can be changed as required.

Dependent Variables

created by the process being observed and whose value cannot be controlled.

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One of the most common functions of visual displays of information is to present the relationship between two variables, such as in a graph. An independent variable is some measurable entity that is available (i.e., can be measured) at the start of a process and whose value can be changed as required. A dependent variable is one that is created by the process being observed and whose value cannot be controlled. The dependent variable is generally represented by the y-axis and is expected to change in response to a change in the independent variable, represented on the x-axis. The number of hours of sleep a student gets each night, for example, could be thought of as an independent variable, while some measure of academic performance, maybe grade point average, would be a dependent variable.

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1.15 Statistics

A set of analytical and mathematical tools designed to help researchers gain understanding from the data they gather.

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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.

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Drawing conclusions based on limited observations is risky.

Measuring a greater number of people will generally help us draw more accurate conclusions about human height.

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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 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 1-20 Drawing conclusions based on limited observations is risky).

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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

“Correlation is not causation.”

Statistical analyses can help us to organize and summarize.

Statistics can help us evaluate whether differences between a treatment and control group can be attributed to the treatment rather than random chance.

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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). 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.

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Examples of false “scientific evidence”

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.

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Thinking scientifically can prevent us from being fooled by false ‘scientific claims.” Two common types of “scientific evidence” are pseudoscience and anecdotal evidence. Pseudoscience is all around us, particularly in the claims made on the packaging of consumer products and food .

Pseudoscience capitalizes on a belief shared by most people: that scientific thinking is a powerful method for learning about the world. The problem with pseudoscience is that the scientific bases for a scientific-sounding claim are not clear. The claims generally sound reasonable and they are persuasive in convincing people to purchase one product over another. But one of the beauties of real science is that you never have to just take someone’s word about something. Rather, you are free to evaluate their research methods and results and decide for yourself whether their conclusions and claims are appropriate.

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Pseudoscience

“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.

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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.

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Anecdotal Observations

do not include a sufficiently large and representative set of observations of the world

data are more reliable than anecdotes

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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 1-23 Headline news.

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Science is One of Several Approaches to the Acquisition of Knowledge

The scientific method is, above all, empirical.

Value judgments and subjective information are outside the realm of science (religion and faith)

Cannot generate moral statements and ethical problems

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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.

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Two Unifying Themes in Biology

Hierarchical organization

The power of evolution

Bio100 NU Phelan

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In this guide to biology, as we explore the many facets of biology and its relevance to life in the modern world, you will see two unifying themes recurring throughout:

* Hierarchical organization: Life is organized on many levels within individual organisms, including atoms, cells, tissues, and organs. And in the larger world, organisms themselves are organized into many levels: populations, communities, and ecosystems within the biosphere.

* The power of evolution: Evolution, the change in genetic characteristics of individuals within populations over time, accounts for the diversity of organisms, but also explains the unity among them.

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Four Chief Areas of Focus

The chemical, cellular, and energetic foundations of life

2. The genetics, evolution, and behavior of individuals

3. The staggering diversity of life and the unity underlying it

4. Ecology, the environment, and the subtle and important links between organisms and the world they inhabit

Bio100 NU Phelan

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These two major themes connect the diverse topics, as we make our way through four chief areas of focus. <Please read the slide>

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