Welcome to Science

1. Welcome to Science Introduction

2. Science defined • A popular view of science is that it is any systematic approach, expounded with technical jargon. (Look at all the big words in your text book!) • A professional view of the definition of science is that it is a rigorous, systematic use of observations and logic to attempt to support or falsify possible explanations of natural phenomena.

3. Important characteristics in practicing science…. • Curiosity (Where it all begins!) • Honesty • Openness • Skepticism • Can anyone think of a relevant, current topic people are debating?

4. Scientific Method Great things are accomplished one step at time.

5. Science is a way of doing things, a way of thinking. • Science starts with observations of happenings in nature. • Look at the world around you and use your senses or machines which are basically extensions of those senses to make observations. • Observations lead to asking questions.

6. In a nutshell…

8. The Scientific Method – The beginning… observations lead one to ask a question… • Curiosity leads to asking questions. • Why is the sky blue? • I wonder what happens if I mix these two things? • Can I fly like a bird? • WHY! You drove your parents crazy with questions! (Are humans born with innate curiosity?)

9. Research • Look to see if someone has the answer to your question! • No… so learn everything you can about your question so you can develop a possible answer/solution.

10. Develop a hypothesis • A hypothesis is often called an educated guess…. What do we mean by educated? • A hypothesis is a tentative explanation (to the question you asked) that accounts for a set of facts and can be tested by further investigation.

11. Design and perform the experiment • There are a variety of experimental designs but in general experiments have independent variables, control variables and a dependentvariable. • It is important to record procedures, observations, and data in an accurate and readable manner (graphs, charts, tables, etc.). The lab book is a legal document! • Often, scientists repeat experiments to determine if they get the same findings.

12. What are variables? • Variables are things that we measure, control, or manipulate in research. They differ in many respects, most notably in the role they are given in our research and in the type of measures that can be applied to them.

13. Independent Variables (a.k.a. Experimental Variable) • Independent: the variable the experimenter manipulates • Terms are also used in studies where we do not literally manipulate independent variables, but assign subjects to "experimental groups" based on some pre-existing properties of the subjects. • For example, if in an experiment, males are compared with females regarding their white cell count (WCC), Gender could be called the independent variable and WCC the dependent variable.

14. Control Variables/Control Group • Those variables which are not under investigation but may have an impact on the outcome if not taken into account • Ex. Type of plant • The use of a matched or similar group which is not exposed to the experimental variable. The control group is exposed to all conditions of the experiment except the experimental variable. • Ex. Use of fertilizer • An attempt is made to hold all other variables except the dependent variable constant… hence the term “control”!

15. Dependent Variables • Dependent variables are those that appear to be directly impacted by the independent variable. • Ex. Rate of growth

16. So…. • Generally speaking, the ultimate goal of every research or scientific analysis is finding relations between variables. The philosophy of science teaches us that there is no other way of representing "meaning" except in terms of relations between some quantities or qualities; either way involves relations between variables. Thus, the advancement of science must always involve finding new relations between variables.

17. Double check! • Scientific researchers are expected to critically assess the quality of data including possible sources of bias in their investigations’ hypotheses, observations, data analyses, and interpretations. • What is bias?

18. Draw conclusions • Determine if the hypothesis was correct, partially correct or incorrect. • In reality, the process leads to greater understanding of the question/problem even if the hypothesis was incorrect! • Finally, share the findings with the scientific community. Scientists use practices such as peer review and publication to reinforce the integrity of scientific activity and reporting.

19. Scientists learn from failure. Watson and Crick made the first model of DNA, the chemical of genes – wrong that is! They got it right on the next attempt. Debate and revision of ideas in science is a natural process. Even as scientists debate the processes of evolution, the vast majority accept that it has happened. Debate is not evidence that the theory of evolution is fatally flawed.

20. But, is that the end of it????? • It is important to recognize that different explanations often can be given for the same evidence! • Because of this, further understanding of scientific problems relies on the design and execution of new experiments which may reinforce or weaken opposing explanations. • Testing, revising, and occasionally rejecting new and old theories never ends.

22. Two ways of describing the Scientific Method: • Formal definition • Observe phenomena • Ask questions • Form hypothesis • Perform experiments • Check hypothesis • In practice • Make a guess • See if it works! “Science is what scientists do, and there are as many scientific methods as there are individual scientists.“ P.W. Bridgman (Nobel Prize in Physics 1923)

23. There are no final answers in science. • Knowledge is infinite. Atoms are infinitely small and the universe is infinitely large. We can never know anything completely.

24. Examples

25. Everyday Science

26. Everyday Science

27. Medical Science

28. A few good rules to recognize junk science are: • Doubt everything: Be skeptical of scary health news. In science, credibility is earned, not self-evident. You think, therefore you doubt. • The Yoke's on them: The burden of proof is always on the party trying to prove a point. "Better safe than sorry" can be an excuse to push junk science. • Speculation isn't science: Watch out for junk scientists who try to pass off speculation as reasons to hit the panic button. Giveaway terms include "may", "might', "could", "if", "possibly", "perhaps", "potentially", and the like. When uttered by someone with a clear vested interest in promoting a health scare, these words can indicate junk science. • Anecdotes aren't data: Anecdotal data are essentially a single or a few observations. Anecdotes are designed to appeal to your emotions and fears. It's a ruse to get you to put your brain in neutral and overlook the facts.

29. Example 1: • Former surgeon general Antonia Novello claimed in a May 1990 speech that 3,000 "kids" start smoking every day. The statistic originated from researchers at the U.S. Centers for Disease Control and was published in the Journal of the American Medical Association in 1989. If you read the actual study, you'll discover that only persons aged 20 years and older are included. Surely you understand why anti-smoking advocates don't claim "3,000 twenty-something kids start smoking every day". • "Smoking is Too Often a Child's Decision," St. Petersburg Times, August 5, 1990 • J.P. Pierce, M.C. Fiore, T.E. Novotny, E.J. Hatziandreu, R.M. Davis, "Trends in Cigarette Smoking in the United States: Projections to the Year 2000," Journal of the American Medical Association, January 6, 1989, pp. 61-65

30. Example 2: • The EPA claimed in 1996 that fine particulate air pollution kills 20,000 Americans annually. The basis for the estimate was a statistical study comparing death rates among geographic areas with varying levels of pollution. There were no clinical evaluations of any of the deaths included in the study and the researchers didn't know whether air pollution caused or contributed to any of the deaths or have any idea of how much fine particulate pollution any study subject inhaled.

31. Example 3: • in 1997 students and staff at two primary schools in northern Italy were hospitalized with gastrointestinal illness. All students and staff ate food from the same caterer. Researchers found that for one particular food served (corn & tuna salad), the data were as follows: • Therefore, those who were ill were 33 times more likely to have eaten the corn & tuna salad. The researchers began to think that the corn & tuna salad were responsible for the illness. But, because statistics aren't science, the researchers confirmed the results scientifically by testing the actual food and finding the "bug" that caused the illness.

32. The Rule of Falsifability • This a general rule about any claim being made. It must be possible to conceive of evidence that would prove the claim false. (Karl Popper first suggested this in the 1930’s) • It may sound paradoxical, but in order for any claim to be true, it must be falsifiable. The rule of falsifiability is a guarantee that if the claim is false, the evidence will prove it false; and if the claim is true, the evidence will not disprove it (in which case the claim can be tentatively accepted as true until such time as evidence is brought forth that does disprove it). The rule of falsifiability, in short, says that the evidence must matter, and as such it is the first and most important and most fundamental rule of evidential reasoning.

33. Show me the evidence! The Skeptic's Dictionary: A Collection of Strange Beliefs, Amusing Deceptions, and Dangerous Delusions (John Wiley & Sons 2003) by Robert Todd Carroll

34. Science • Ultimately, it is not about a method, it is all about attitude! • The attitude is one of inquiry, experimentation, honesty, and faith that all natural phenomena can be explained.