Notes on the Web - Unit One - Part 2
The Methods and Types of Explanations of Science
Bruce G. Stewart
General Objectives and Study Guide
Your objectives for these Notes on the Web and associated readings and exercises are:
Philosophies of Science
Philosophers have debated the question of what constitutes science for centuries. Views have differed throughout the history of science. As scientific knowledge has increased there has been a concurrent evolution of scientific philosophy. Three influential examples are the Baconian Philosophy, the Popperian Philosophy, and the Kuhnian Philosophy. All of these philosophies have addressed certain aspects of scientific methods and thought. All have contributed to the current practices in science. Contemplate this quote from Novum Organum by Francis Bacon in 1620 The Great Books Foundation 1955):
For what a man had rather were true he more readily believes. Therefore he rejects difficult things from impatience of research; sober things, because they narrow hope; the deeper things of nature, from superstition; the light of experience, from arrogance and pride, lest his mind should seem to be occupied with things mean and transitory; things not commonly believed, out of deference to the opinion of the vulgar. Numberless in short are the ways, and sometimes imperceptible, in which the affections color and infect the understanding.
Bacon recognized the importance of bias in influencing our perspective of nature, and he argued for a more logical approach to studying nature. Popper was a great philosopher who, in a nutshell, viewed science as a process of attempting to refute theories/hypotheses. Those explanations that can be falsified are rejected, while those that are not falsified with continuing and vigorous effort are provisionally accepted. Kuhn looked at science as a process involving the development of generally accepted "paradigms" or theories that are subsequently tested extensively in a process of "normal science." Eventually, however, if the paradigm is not correct, anomalous data will appear. The scientific community will not, of course, cast out a theory simply because there are some unexplained data. However, if enough anomalous data are gathered through many studies, a "paradigm shift" will eventually occur in which the former prevaling view will shift to a revolutionary new explanation (Kuhn 1970).
Scientific Methods: Not Just One!
The great biologist and philosopher, Ernst Mayr, described three general categories of scientific methods (observational, comparative, and experimental) rather than a single "scientific method" as is so often presented in textbooks. It is overly simplistic to describe experimental science as if it were the single "Scientific Method." The following sections briefly describe, explain and illustrate the three general types of science methods discussed by Mayr (1982, 1988) as I have come to understand them.
Observational Method
Observation of nature is the fundamental basis of science. It may be thought of as the "what is" method. Collection of observational data must precede comparative and experimental methods before these can be applied in science. Mayr (1988) clearly points to the important role of observation in the following statement.
In fact, since the days of Copernicus and Kepler, observation and comparison have been exceedingly successful methods in such physical sciences as astronomy, geology, oceanography, and meteorology. And in biology, where observation and comparison have always been of paramount importance, experimental methods have been incorporated into the methodological repertory of many originally observational disciplines, including ecology and ethology.
Observation has dominated the early stages of most scientific disciplines. But even within established disciplines, such as astronomy, observation continues to produce important knowledge. In health science-related areas such as human anatomy, observation was the primary method used to describe the construction of the body. My own specialty area of ecology has been criticized at times as being a weak science because of the once rarity of rigorous experimental methods. Yet even today, there is a tremendous need for observational data in ecology. Thorough natural history studies, for example, are needed for a vast array of species.
Comparative Method
Comparison of data sets is a powerful method for discovering patterns in nature. Suppose, for example, you wish to determine if smoking tobacco (as the independent variable) is correlated with the prevalence of lung cancer (as the dependent variable) in humans. Since experimental exposure of humans to tobacco smoke for, say, a 30-year periods is both ethically unacceptable and logistically unfeasible, some other method of investigation must be used. The comparative method is ideal. Many humans have exposed themselves to significant amounts of cigarette smoke on a daily basis for more than 30 years. Thus, in effect, they have applied the independent variable of interest in our question about the smoking/lung cancer relationship.
We may hypothesize an answer to our question as follows: Inhalation of tobacco smoke by smoking one or more packages of cigarettes per day for thirty years or more increases the chance of getting lung cancer. Notice that this hypothesis is not a question! It is possible to apply the comparative method to determine if our hypothesis is supported. To do this, we must gather data on two groups of humans: a) an experimental group of people who have subjected themselves to our independent variable (smoking one or more packs of cigarettes daily for 30 or more years) b) a control group of people who have not smoked. By comparing the incident of lung cancer, which is our dependent variable, we can determine if there are significantly more cases of lung cancer in the experimental group. If this is the case, then we may say that our study supports our hypothesis. If we found no difference in the lung cancer rates between our two groups, then our hypothesis would not be supported.
Suppose our control group had been exposed to other potential cancer causing variables or possessed cancer correlated characteristics that our experimental group had not. Second-hand smoke, asbestos fibers, air pollution, stress, age, and many other factors have been associated with the prevalence of lung cancer. Even "third-hand smoke" (exposure to residues left on the bodies of smokers, clothing, upholsery, etc.) is now being studied as a likely contributing factor to smoking-related disease! (see: http://www.scientificamerican.com/article.cfm?id=what-is-third-hand-smoke) To understand the possible relationship of smoking to our particular hypothesis, we must control the effect of such potentially confounding variables by keeping both the control group and experimental group the same in these respects. Preferably, neither group would have been exposed to these other potential cancer causing variables. In the case of age, both groups should be composed of the same age groups. These kinds of variables that could confuse our results but do not because we control them are called controlled variables. It is very important to understand why they must be controlled.
The comparative method is very good for finding patterns that may later be worthwhile to study in a "cause and effect" experimental study. Or, sometimes this method may simply be the most desirable for various reasons. Noy-Meir (1970) as cited in Ludwig and Reynolds (1988), for example, stated that:
Community ecologists are often interested in obtaining information pertaining to a large number of variables in a community, but without imposing any manipulations on theses variables. That is, we usually follow an observational [implied comparative also] approach, which is inductive, nonexperimental, and multivariate.
The value of the experimental method is described in the next section.
Experimental Method
This method is the "typical textbook version" of the "scientific method. As we have seen, other methods are commonly used in science. However, the experimental method is especially powerful for determining cause and effect. Just because a pattern of correlation exists between two variables does not mean that one necessarily caused the other. An often-quoted example of such a "spurious correlation" is the increase in numbers of Baptist ministers that is correlated with the increase in violent crimes during the past several decades! Of course, the correlation does not mean that Baptist ministers cause violent crime! Both increases are also correlated with a third variable, namely, an increase in overall population.
In the case of cigarette smoking and lung cancer, we wish to make sure that correlations discovered by the comparative method are not spurious. Experiments can demonstrate cancer-causing effects of components of cigarette smoke on animal tissues and cells in the laboratory. Manipulating independent variables (nicotine, for example) has done this in controlled experiments. The experimental group is exposed to the independent variable, while the control group is not. Cause-and effect is suggested if cancer-related dependent variables (such as incidence of cancer or death from cancer) increase in the experimental group but not the control group. This is valid, of course, only if we have controlled other potentially confounding variables.
The experimental method, like the comparative method, includes the processes of:
An Example to Illustrate the Use of Observational, Comparative, And Experimental Methods in Animal Behavior
Dr. Douglas Mock of the University of Oklahoma is well known in the study of animal behavior. One of his special interests is a behavior termed "siblicide." Siblicide refers to the phenomenon of siblings (brothers or sisters) killing each other. Why would this behavior occur? Wouldn’t it be evolutionarily advantageous for parents to intervene to save their own offspring? Is siblicide a rigid behavior that cannot be altered in the species that practice it? If it can be altered, what factors regulate the animals’ decisions?
Dr. Mock has performed some elegant field experiments to answer these questions. In 1980, I had the opportunity to visit one of Dr. Mock’s field research sites at Matagorda Bay, Texas. It was there that I first learned the siblicide aspects of the natural history of the Great Blue Heron and the Great Egret. You may find the results of some of Dr. Mock's work in the primary scientific literature (Mock 1985,1987; Mock and Parker 1986, and others). As I tell this story, you should keep in mind the following terms and concepts: hypothesis, control group, experimental group, manipulated (= experimental) variable, controlled variables, and dependent variable.
Before we explore Dr. Mock’s research, it would be helpful to learn about "natural history." Natural history is an area of biology defined by Bates (1990) as " the study of life at the level of the individual—of what plants and animals do, how they react to each other and their environment, how they are organized into larger groupings like populations and communities." Bates goes on to explain the problems of natural history.
It is amazing enough to stop and look at a forest or at a meadow—at the grass and trees and caterpillars and hawks and deer. How did all of these different kinds of things come about; what forces governed their evolution; what forces maintain their numbers and determine their survival or extinction; what are their relations to each other and to the physical environment in which they live? These are the problems of natural history, problems that concern us ourselves as animals and that concern us even more as originators of this thing we call civilization—which is, after all, merely a rather special sort of an animal community.
Thus, Dr. Mock’s research on the Great Blue Heron and Great Egret was first and foremost based on knowing what these species "do." Observational and comparative data show that these species are water-associated birds with very similar characteristics. They are so similar that they are placed in the same taxonomic family. Both species are tall birds with long legs for wading, long necks for "striking" like snakes, and long sharp bills for spearing and capturing aquatic prey. Both species are colonial nesters, and Dr. Mock found a number of islands in Matagorda Bay on which both species nested in large numbers. This was an ideal location for research on their behavior.
Field observations indicated that both species lay an average of about four
eggs per nest. Both species began incubation of the eggs after the first egg
was laid. Hatching in both species occurred "asynchronously," meaning
that the first egg laid was the first egg to hatch and the others typically
hatched in order about a day or two after the previous egg.. This resulted in
developmental advantages for the earlier-hatching chicks since the first chick
(designated "A" chick) would be four to five days old by the time
that "D" chick hatched.
A most interesting observation was that there was an amazing difference in the behaviors of Great Blue Heron chicks versus Great Egret chicks. Great Blue Heron chicks showed low levels of aggression toward each other. Great Egret chicks were highly aggressive to the point that in 33-50% of the nests studied, the youngest chick was killed due to aggression by their older siblings! Herein lay a general question, "Why would two otherwise similar species have nestlings that exhibit such differences in behavior?"
How do you imagine that aggressive behavior could be put into precise mathematical terms? Hundreds of aggressive encounters were observed. Dr. Mock and his research assistants distinguished specific categories of aggression and related behaviors. For example, a strike or blow occurred when one chick struck another chick with its bill. A retaliation was a strike back by the second chick. Retreats occurred when a chick attempted to move away from its aggressor. These and other categories allowed mathematical quantification of data that could later be statistically analyzed and compared. In a sense, the observers were "judges’ such as in a human boxing match. Dr. Mock's research team recorded "up to 127 consecutive blows with the bill, usually directed at the loser's nape and base of the skull" (Mock 1987).
One question of interest was "Is food type related to the magnitude of aggressive behavior?" Dr. Mock and his research assistants observed a difference in the size of food items that parent birds fed to their nestlings. Dr. Mock stated, "Heron chicks ate portions of very large fish that could not be monopolized, while young egrets consumed discrete boluses of tiny fish that could better monopolized through fighting." Dr. Mock suspected that it would be possible for an older individual nestling to monopolize discrete boluses (a sort of fish meatball!) by driving younger nestlings away at feeding times. He suggested that a scattering of larger food items could not be easily dominated.
A prediction based on the "food type" scenario is that nestlings should fight when the benefits (i.e. greater caloric intake) outweigh the costs (e.g. injury or less feeding success). Allow me to use an analogy to illustrate this logic. Suppose you were in a room with a group of three other students. Your professor walks in and throws $100 to the floor for anyone to take. Imagine your strategy for getting the most money if it were in the form of a separate ten dollar bills. How might this differ if the money were in the form of 100 one dollar bills all held together (like a bolus) by a band?
To test the food type hypothesis, Dr. Mock conducted an ingenious field experiment. Great Egret eggs where switched with Great Blue Heron eggs in clutches at the same stage of incubation. Then the aggressive behavior of the chicks that resulted was quantified. The outcome was clear. When raised on food items of their close evolutionary "cousins," the chicks reversed their typical behaviors. Great Blue Heron chicks exhibited high levels of aggression and siblicide; Great Egret chicks became more peaceful!
This example of field experimentation is really two experiments in one. Behavior of Great Egret chicks was compared in a manipulated condition (i.e. raised on Great Blue Heron food type) to that in a natural condition (i.e. raised on Great Egret food type). The same was true for the Great Blue Heron chicks.
Now that the story is told, identify the variables involved in this example. Fill in the following spaces:
- ________________________________
- ________________________________
- ________________________________
To conclude this exercise, be a critic. What variables do you think would have been especially hard to control? What do you think a scientific reviewer might ask about, if all she/he knew were the details presented here?
True Story: A Questionable Conclusion Drawn from a Small Sample Size and Lack of Controlled Variables
On 29 December 1992, I met Señor Humberto Ramírez García in a small, isolated desert settlement, Santa Tecla, in the northern Mexico desert basin of Cuatro Cienegas. Señor García said that he knew the best way to treat snakebites. This was the method. Take a greasy kitchen rag from your house and place it loosely around the neck of the snakebite victim! That was it! This would, according to Señor García, save the life of the victim.
Senor García had data to support his claim that the treatment works. He said he had four dogs that at various times were bitten by snakes. In three cases he wrapped the dirty kitchen rag around their necks, and they lived. In one case, because they were far away from the village, he could not get the rag; the dog died. Thus, dirty kitchen rags work as a treatment for snakebites!
What alternative hypotheses could explain Señor García's data? Could variables other than treatment with the kitchen rag produce such results? Write three possibilities in the following spaces.
_____________________________________________
_____________________________________________
_____________________________________________
With a little thought, we can quickly realize that many variables could influence the probability of dying from snakebite. Species of snake, body location of the bite, age of the victim, body weight of the victim, and physical health of the victim are a few variables that come to mind. Senor Garcia apparently did not consider these possibilities in coming to his conclusions.
Even if we assume that the "treatment" was the only variable that was different between the dogs that lived and the one that died, there is another fatal flaw with Senor Garcia’s data base: sample size. We must considering random or stochastic effects that can produce misleading patterns in small data sets. This is addressed in the following section.
Statistics, Probabilities and Random Effects
Some say that statistical techniques are useless because statistics can be used to come to any conclusion. This in itself is flawed thinking. As I mentioned in the preface of this manuscript, honesty is essential in science. Well-informed, honest application of statistical techniques provides a powerful and essential tool for making sense of our data. Here is a simple example to illustrate the importance of statistics.
Suppose I offered you an opportunity to bet a month’s wages to win a million dollars for determining whether a coin had "head-and tail" sides or was a "two-headed" coin. The catch is that you can only see one side of the coin at a time, after a flip. Would you bet after one flip if the result was head? What if you were offered two flips and both results were heads? Three heads? Four heads? How many heads in a row would you require before concluding that the coin was two-headed? At what point would you risk your month’s wages?
Two answer this question in an informed way, you would need to consider the probability of getting heads on different numbers of consecutive flips if in fact the coin had a head and a tail. How do you calculate these values? Well, the probability of getting one head if the coin also has a tail side is 0.5 (or 50%). To calculate the chance of getting two heads in a row, multiply the probability of the first head event (0.5) times the probability of the second head event (0.5) for a probability of 0.25 (or 25%). For more heads results we continue to multiply. The probability of a head occurring three times in a row would be 0.125, for four heads it would be 0.0625, and for five heads it would be 0.03125 (or 3.125%).
Any gambler worth her salt understands probabilities. The same is true of scientists. Science places its "bets" on the explanations that have the greatest probability of being true. Which brings me to another point. In the coin flip example, you could never be 100% sure that it was a two-headed coin if all your data were heads! There would always some probability, however miniscule, that chance alone produced very improbably results. In our everyday life we deal with the same issues in our decision-making. In everyday living we routinely make decisions with which we are not 100% certain. Yet we do so with certainty! In science we likewise accept the most probable answers and explanations. When we say that we are not 100% certain, it does not mean that we are guessing! Our best tested theories are as certain as the "facts" as interpreted by the layperson.
Enemies of Logical Thinking: Bias and Denial
The Earth is flat! At least that is what Charles K. Johnson, recently deceased president of the International Flat Earth Research Society claimed.. Sound ludicrous? It is! But Charles Johnson believed and many other members of this society believe that the Earth is flat. How could sincere people be so mislead? Bias and denial seem to be major factors in their mislead logic. Let me illustrate. Over 2000 historic records exist for lighthouses that provide information on height of the structures and distances such lighthouses were said to be visible from distant ships (Schadewald 1992). Visibility distances would be much longer if the Earth were flat versus if the Earth were round, since the curvature of the Earth would require ships to be much closer before rising to a clear line of sight. Less than 1.5% of historic records are consistent with a flat Earth theory, while over 98.5% support a globe-shaped theory. Yet flat-earthers only accept the data consistent with their pre-conceived belief that the Earth is flat!
The vast majority of people on Earth would think the flat-earthers are lunatics. However, the same people exhibit the same illogic in everyday life! What do I mean by this? Consider the following commonly heard statements. "I know some people who smoked their whole life and didn't get lung cancer; medical researches exaggerate when they say smoking causes lung cancer." "So what that I am overweight; not every overweight person has heart troubles." "They say heart trouble is in your genes, so it doesn’t matter if I exercise." "One time they say this and another time that! I don’t think it matters what I do. I’ll die when my time comes anyway." "I can’t be an alcoholic, I have a job."
Science must eliminate bias and denial from the scientific process in order to come to objective valid conclusions. You too must eliminate bias and denial in your own thinking in order to come to objective, valid conclusions! The following section discusses some procedures of science that help accomplish this.
Verification Processes
Before we enter into this section, let us remember that science, like other valued areas of human endeavors, must possess honesty, open-mindedness, and the willingness to use these qualities to conduct legitimate scientific research that meets the criteria of science. But scientists are, after all, just human. Science is distinguished by how this "human fallibility" of individual scientists is dealt with in to prevent errors from being perpetuated too long. Let me quote from Stanovich (2001) who credits Jacob Bronowski on this general topic:
Jacob Bronowski (1973, 1977) often argued in his many writings that the unique power of science to reveal knowledge about the world does not arise because scientists are uniquely virtuous (that they are completely objective; that they are never biased in interpreting findings, etc.) but instead it arises because fallible scientists are immersed in a process of checks and balances--in a process in which other scientists are always there to criticize and to root out the errors of other scientists.
The materials below very briefly describe some of those important "checks and balances" that help set a standard in science.
Repetition. Our confidence in the results of an observation, experiment or comparative study is greatly increased when we see the same basic pattern again and again. Although the researcher may repeat her/his works to determine the consistency of the results (and this is important in later publishing), it must also be possible for other researchers to duplicate the results if they try. Know why something must be repeatable to be called scientific knowledge.
Publication Process. We will discuss the publication process in science in detail in class or as a Lab Activity. Know how the process works. Here are some helpful terms and points related to this: journal, editor, peer reviewers (referees), revision process, rejection of papers, literature cited, qualifications of authors, typical sections of papers (e.g. introduction, materials and methods, results, discussion and conclusions). Here is a figure we will clarify in class showing a common way a manuscript might "flow" through the publication process.
You will examine peer-reviewed scientific journals in class. CLICK HERE FOR MORE INSTRUCTIONS. Consider how these articles differ from "popular" literature for general reading. Some journals have very high rejection rates. How does this represent, as Carl Sagan has said, a boon to science as well as a favor to the author?
Types of Scientific Generalizations, Explanations, and Predictions
Briefly, the terms law and principle in science apply to generalizations about phenomena consistently observed to occur in nature. A theory provides an explanation of a phenomenon. Theories often postulate mechanisms that cannot be directly observed but can be tested indirectly against predictions made about the observable phenomenon. Theories often describe the "ultimate" causes of phenomena. An individual testable prediction that is a possible or probable answer to a specific question is referred to as a hypothesis. Thus, we may state what we predict based on theory, and then determine through the observational, comparative or experimental methods if our prediction is supported. A well-tested theory has a foundation supported 1000's or 10,000's of tests of many different pertinent hypotheses. An analogy of the relationship of hypotheses to a theory can be made of the relationship of piers supporting a house on the coast. A single pier would be a weak support. Four piers might hold the house up, but is still very tenuous. A thousand piers would be a firm foundation indeed! When their are a few weak piers, the foundation remains strong. Likewise, a theory remains strong when the weight of supporting evidence is broad.
The following definitions come from the National Academy of Sciences.
Glossary of Terms Used in Teaching About the
Nature of Science |
| Fact: In science, an observation that has been repeatedly confirmed. |
| Law: A descriptive generalization about how some aspect of the natural world behaves under stated circumstances. |
| Hypothesis:A testable statement about the natural world that can be used to build more complex inferences and explanations. |
| Theory: In science, a well-substantiated explanation of some aspect of the natural world that can incorporate facts, laws, inferences, and tested hypotheses. |
To reiterate, many well-tested theories have been tested literally tens of thousands of times. They fully quality in everyday laymen’s terms as "fact" even though we continue to use the word "theory". Unfortunately, many people think of "theory" only as an educated guess, which it is not in science.
Which of the above categories of explanation are supported by adequate evidence to say they are most probably correct? Are any of these beyond reexamination? Does the open-mindedness of science with respect to such possibilities mean that we expect our well-tested theories to be overturned?
Additional Critical Thinking Exercises
At least two critical thinking exercises will be assigned or conducted in class, lab, or over Internet. The first two are given below.
The Downfall of Agriculture in the Soviet Union: The Case of Lysenko and Marxism Some would say that
teachings in science education should give equal time to certain political
and religious beliefs. Some would even go so far as to say that
scientific views that conflict with certain political and religious
beliefs should be censored. However, history teaches us that time
and time again, human ignorance of nature has resulted in disasters, human
suffering and even the downfall of entire cultures.
Take the case of
Trofim D. Lysenko in the Soviet Union in the 1930's, for example (as
described by Futuyma, 1982). Lysenko, a dedicated Marxist,
thought that Mendelian genetics and natural selection could not be true
because this would mean that individual organisms could not improve their
own genetic makeup. This was in conflict with Marxist doctrine which
Lysenko interpreted to mean that nature, like societies and humans, must
be able to improve toward perfection. Thus, he believed in the
inheritance of acquired characteristics. He thought that crops could
be improved for cold climates simply by growing them in colder conditions
for a single generation. Of course, the evidence then as now showed
that this was not the case.
Had Lysenko's views on
biological inheritance simply represented ideas for further testing,
science and agriculture in the Soviet Union could have proceeded on
without disaster. However, Lysenko was a powerful politician who
forced his views into practice and within a decade the best
scientists in the Soviet Union had been imprisoned, executed, or
silenced.(Futuyma 1982). The results were agricultural
disaster and severe setbacks in Soviet biological science for many
decades.
Our beliefs, whatever they may be, simply do not override the laws of nature. Our fate as a free democratic society might be no different than the Soviet Union's if we infect our proven scientific process with pseudoscientific belief systems (i.e. cultural pathogens). At the very least it will begin to erode our progress in gaining better understanding of living systems. |
An Online Scientific Method Lab Exercise
Visit the web page at the following link: http://biology.clc.uc.edu/courses/bio104/sci_meth.htm Read all of the web page and then do the exercise that involves selecting a hypothesis to test regarding why plants tend to grow toward windows. Type up the following to submit to me through Turnitin.com:
Use a readable format when you prepare your report. List each of the items above as sections of your report. Include your name, date, and name of exercise in the upper left corner of the first page. If you discover that you did not properly test your hypothesis, repeat the exercise and include the same information on your second try and other tries as required until you get it correct. Don't worry if you make a mistake the first time. No points will be deducted if you ultimately get it correct. However, you will have point deductions if you tested your hypothesis in some way that is irrelevant or flawed. You will also be graded on the format and thoroughness of your report.
Note: The only part of the web page at the link (http://biology.clc.uc.edu/courses/bio104/sci_meth.htm) that you do not have to complete is the group exercise described in the last paragraph of that site.
Credit to author: J. Stein Carter, Claremont College at the University of Cinncinnati
Additional Internet Resources
Dr. Jon Baskin's Notes at Texas A&M University Kingsville - (Specifically scroll done in Dr. Baskin's page to the section on "Scientific Method.")
Cited or Related Literature
Bacon, Francis. 1620. Novum organum, Book I. IN The Great Books: Third Year, Volume Six, Number 10. The Great Books Foundation. Chicago, Illinois. 86pp.
Bates, Marston. 1990. The Nature of Natural History (originally published by Charles Scribner's Sons in 1950) With a new Preface by Henry S. Horn. Princeton University Press. Princeton, New Jersey. 321pp. ISBN 0-691-02446-4.
Bronowski, Jacob. 1973. The ascent of man. Little, Brown. Boston, Massachusetts.
Bronowski, Jacob. 1977. A sense of the future. MIT Press. Cambridge, Massachusetts.
Futuyma, Douglas. 1982. Science on trial: the case for evolution. Pantheon Books, New York.
Kuhn. Thomas S. 1970. The structure of scientific revolutions, 2nd ed, enlarged. University of Chicago Press. 210pp.
Ludwig, John A., and James R. Reynolds. 1988. Statistical ecology: a primer on methods and computing. John Wiley & Sons. New York. 337 pp + diskette.
Mayr, Ernst. 1982. The growth of biological though. Harvard University Press. Cambridge, Massachusetts.
Mayr, Ernst. 1988. Toward a new philosophy of biology. Harvard University Press. Cambridge Massachusetts. 564 pp.
Mock, D. 1985. Siblicidal brood reduction: the prey-size hypothesis. American Naturalist 125:327-343.
Mock, D. W. 1987. Siblicide, parent-offspring conflict, and unequal parental investment by egrets and herson. Behavioral Ecology and Sociobiology. 20:247-256.
Mock D.and G. Parker. 1986. Advantages and disadvantages of egret and heron brood reduction. Evolution 40:459-470.
National Academy of Sciences, Working Group on Teaching Evolution. 1998. Teaching about Evolution and the Nature of Science. National Academy Press, Washington, D.C. (Online at: http://www.nap.edu/readingroom/books/evolution98 accessed on September 10, 2005)
Noy-Meir, I. 1970. Component analysis of semi-arid vegetation in southeastern Australia. Ph.D. Dissertation, Australian National University Canberra.
Overton, William R. 1982. Judgment, injunction, and opinion for McLean v. Arkansas Board of Education. US District Court. Arkansas. 5 January 1982.
Schadewald, Robert J. 1992. Looking for lighthouses. Creation/Evolution. National Center for Science Education. 12(2), Issue 31, Winter 1992.
Stanovich, Keith E. 2001. How to think straight about psychology, 6th ed. Allyn and Bacon, Boston. 256 pp.
© 1999, 2005, 2007, 2009 Bruce G. Stewart
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