“The” Scientific Method (chapter 1 of text)

1. “The” Scientific Method (chapter 1 of text) • Observation/Question about the World • Hypothesis • Predictions based on hypothesis • Test • Evaluate results • Generate new hypotheses and repeat process.

2. Observation/Question • First step. • E.g. It looks as if the coastlines of South America and Africa would fit together. Why might that be? • Wasps have yellow and black striped bodies that make them conspicuous. Is there an advantage for wasps in being brightly colored?

3. Hypothesis • The hypothesis is a tentative EXPLANATION for your observations or an ANSWER to your question. • In generating a hypothesis you would use your knowledge of the subject to make an “educated guess” as to what the correct hypothesis is.

4. Hypothesis • For example: • Wasps are brightly colored because it signals that they are dangerous. This deters predators from attacking them.

5. Hypothesis • Scientific hypotheses are TENTATIVE explanations for your observations. • A hypothesis must be modified if new evidence contradicts it.

6. Hypothesis • Hypotheses must be TESTABLE. • “The devil made wasps black and yellow” depends on a supernatural explanation and so is untestable. • You must be able to generate testable predictions

7. Definition of a hypothesis • Putting it all together we get a workable definition of a hypothesis: • A hypothesis is a tentative, testable explanation for your observations.

8. Prediction • Hypotheses are tested by generating predictions based on the hypotheses and testing them. • Predictions about wasp coloration?

9. Prediction • E.g. If wasps are protected by their color pattern then changing their color pattern should make them more vulnerable to predators

10. Prediction • If wasp coloration provides protection then giving that coloration to non-stinging insects should provide them with protection.

11. Prediction • Notice that predictions generally take the form of an IF THEN statement. • IF something is true THEN something else must follow.

12. Test • Predictions must be tested. • If testable predictions cannot be generated an hypothesis is not useful and probably not a scientific hypothesis.

13. Testing predictions • Predictions may be tested through • (i) observational/natural experiments or (ii) manipulative experiments • Observational/natural experiments usually carried out when it is impossible or unethical to carry out a manipulative experiment.

14. Unethical experiments • Examples of unethical experiments?

15. Unethical experiments • When potentially severe harm is done to participants. (e.g. compelling people to smoke to assess effects of tobacco smoke on lung function).

16. Observational/natural experiment • In such experiments data are collected that allow us to test predictions, but the study subjects are not directly manipulated. • E.g. Collect medical histories of people and make comparisons between groups (e.g. smokers and non-smokers, males and females, miners and non-miners, etc.).

17. Observational/natural experiment • Weakness of natural experiments include • difficulty separating cause and effect relationships. Correlation does not imply causation.

18. Observational/natural experiment E.g. Predict that a male bird will mate more often because he has a long tail, which makes him attractive to females. We find a positive relationship between male tail length and how often he mates. Can we conclude that having a long tail increases mating frequency?

19. Observational/natural experiment • No, because we can’t rule out possibility that mating frequently causes his tail to grow longer.

20. Observational/natural experiment • In the Netherlands there is a strong correlation between the number of stork nests on a house and the number of children in the house. • Do storks bring babies?

21. Observational/natural experiment • Sadly no! • Larger houses have more chimneys for storks to use as nest sites and large families need large houses.

22. Manipulative experiments • Most powerful way to test predictions is with a manipulative experiment. • We can focus on the one factor we think is important and manipulate it.

23. Design of experiments • To test whether wasp coloration provides protection we need to devise an experimental manipulation. • E.g. We could paint over the yellow parts of a wasp’s body to make it all black and see if predators attack it.

24. Experiments • Would this be an adequate experiment?

25. Experiments • We have nothing to compare our results to. How do we know if predators are more or less likely attack our manipulated wasp? • Sample size of one doesn’t tell us much. Need large enough experimental and control groups for meaningful statistical analysis. • What do we need?

26. Controls • We need a CONTROL group of wasps that have not been manipulated to compare our group of manipulated wasps to.

27. Characteristics of control group Control group should be treated exactly the same as the experimental group except that they don’t receive the treatment. There should be only ONE difference between the groups.

28. Controls • Would a group of unpainted wasps be a good control?

29. Controls • Pretty good, but could be better. • Also need to control for possible effects of handling wasps to paint them and the presence of paint on the wasps in addition to the change in appearance of wasps.

30. Controls • Better control might be to paint wasps in clear paint. Then only difference between groups would be the appearance of the control and experimental groups. • Best approach to have two control groups one unmanipulated and one painted with clear paint.

31. Evaluate results • After carrying out the experiment we would analyze the results to see if they support or contradict our hypothesis.

32. Evaluate results • A positive result does not “prove” our hypothesis. • You cannot ever prove a hypothesis is true because it is subject to revision if new evidence is presented.

33. Evaluate results • However, we can become increasingly confident in hypotheses that resist repeated attempts to falsify them. • The more often we test a hypothesis the more likely that the hypothesis is “true.”

34. Generate new hypotheses and repeat process • Results of experiments may falsify hypothesis and so new hypotheses must be produced and the process continues. • Process of science is an ongoing one with frequent testing of ideas.

35. Discovery or descriptive science • Hypothesis-testing not only way science proceeds. “The” scientific method not true. • Careful observation and collection of data can build up our understanding of the world.

36. Discovery or descriptive science • For example, sequencing of the human genome does not involve hypothesis testing nor does describing the behavior of a bird or mapping the distribution of a plant, but all add to human knowledge.

37. Discovery or descriptive science • Descriptive science can lead to important conclusions by a process of generalizing from many observations (inductive reasoning). • E.g. all organisms are made of cells. • “What goes up must come down.”

38. Science and Culture • It is important to remember that science is a human endeavor that is not “pure” and immune from external influences. • The questions that people ask or think that are worth asking are strongly influenced by upbringing, culture and experience.

39. Science and Culture • For example, in studying mating behavior in animals until the 1970’s most scientist’s focused on the importance of male-male competition in determining mating success. Male impala and elephant seals fighting over females

40. Science and Culture • It wasn’t until large numbers of female scientists began working in the field that the importance of female choice of mates was recognized as being of major significance. Choosy female ruffs mate with only the most impressive males

41. Science and Culture • Our assumptions about how the world works are also shaped by culture. • Important to be aware that numerous assumptions (conscious and unconscious) underlie our thinking. • What is an assumption?

42. Assumptions • An assumption is a fact or piece of information you take to be true as a starting point in research. • E.g. testing drugs on mice to see how well the drugs work is based on the assumption that mice and humans are biologically similar and that the drugs will work in a similar manner in each organism.

43. Assumptions • Assumptions may prove to be invalid which can severely limit the usefulness of a piece of research. • For example, a lot of medical research has been carried out on men, but not women based on the assumption that male and female bodies behaved similarly. In many cases the assumption is invalid. For more information see e.g. http://magee.upmc.com/WomenHealth.htm

44. Limits of Science • Science requires that hypotheses be testable and falsifiable and that observations and experiments be repeatable. • Science seeks natural causes for natural phenomena.

45. Limits of Science • Science cannot support or falsify hypotheses that supernatural forces cause, for example, storms or illness because such claims are not testable.

46. Limits of Science • Occam’s Razor: the principle that a simple explanation is better than more complex ones. • As we gain more and more understanding of the causes of storms and disease there is no need to invoke supernatural explanations because simpler explanations are sufficient.

47. Creationism and “Intelligent Design” • The idea of evolution has been harshly criticized by religious fundamentalists since the publication of the Origin in 1859. • This has been especially true in the U.S. • Repeatedly, believers in the literal truth of the Bible have attempted to have alternatives to evolution (i.e., creationism) taught in the public schools and to have the teaching of evolution either banned or restricted.

48. Creationism and “Intelligent Design” • The U.S. Supreme Court has prohibited the teaching of creationism in public schools as a violation of the establishment of religion clause of the Constitution. • Latest attempt to insert creationism into schools is the idea of “Intelligent Design.”

49. Creationism and “Intelligent Design” • The concept of “intelligent design” is outlined most clearly in Michael Behe’s book “Darwin’s Black Box.” • The central idea in “intelligent design” is that some structures in the body are so complex that they could not possibly have evolved by a gradual process of natural selection. These structures are said to “irreducibly complex.”

50. Creationism and “Intelligent Design” • By “irreducibly complex” Behe means that a complex structure cannot be broken down into components that are themselves functional and that the structure must have come into existence in its complete form.