Today is Friday (!), September 6 th , 2013

1. In This Lesson: Scientific Method (Lesson 2 of 4) Today is Friday (!),September 6th, 2013 Pre-Class: What’s a characteristic of a good experiment? (lots of answers here) P.S. Find your Mythbusters worksheet dealies.

2. Today’s Agenda • Some Inspiration • Scientific Method Terminology Defined • The Checks Lab • Where is this in my book? • P. 5, 8-15

3. Some Inspiration • “I never failed once. It just happened to be a 2000 step process.” • Thomas Edison, in reference to his many “failed” attempts to invent the modern electric light bulb. • No one ever learns to walk without falling first. • Basically, I want you to know that I put no pressure on you to be right every time. I’m not grading you on what you say – I’m just trying to help you learn.

4. The Scientific Method • The scientific method can be presented in many or few steps. • Here’s our general one for this class: • Observe [a problem or pattern] • Research [the background info, if any] • Hypothesize [your best guess for an explanation] • Experiment [test your hypothesis] • Analyze [make sure you’re seeing a true pattern] • Conclude [accept or reject your hypothesis, explain]

5. Exploring the Steps • Observe • Being observant is crucial for being a scientist. • You are born with some basic tools for observing. • Scientists have developed other tools for observation too. http://thebeautybrains.com/wp-content/uploads/2006/12/senses.jpg

6. Testing Observation Skills • The Checks Lab!

7. Exploring the Steps • Research • All science is built on previous science. • Finding background information allows you to learn more about the pattern you are seeing.

8. Exploring the Steps • Hypothesize • Develop your best guess as to what could explain the pattern. • Generally “if-then” statements. • Consider all evidence you have researched or observed. • Ensure that your hypothesis is testable! • “falsifiable” • What is not a testable hypothesis?

9. Testable Hypotheses • Discuss with your partner which of the following hypotheses are testable by an experiment: • A: Spiders given caffeine make asymmetrical webs. • B: God created all life. • C: There are no unicorns. • D: Eye color is a trait inherited from one’s parents.

10. About Choice C… • If I were to go to the forest around here and not see a woodpecker, can I say it’s not there? • No, I can only say I don’t have any evidence that it’s there. • The same goes for hypotheses. • It’s more about saying, “Yes, we have evidence,” or “no, we don’t,” than about “right” and “wrong.”

11. Experiment • Test your hypothesis. • Features of a good experiment: • High sample size (n). • In other words, they tested a lot of subjects. • If you tested 100 people, n = 100. If you tested 100 people in two groups of 50, n = 50. • Has a control group and variable groups. • An un-modified sample and a sample being tested. • Only one variable tested at a time. • Sources of error are minimized. • Can be repeated by others. • Procedure is clear.

12. Example Experiment • Hypothesis: • Spiders given caffeine build asymmetrical webs. • Experiment: • Gather 100 spiders of same species. • High sample size, no additional variables. • Give 50 spiders caffeine and water, give other 50 plain water. • Control group (plain water) and variable group (caffeine and water). • Record procedure clearly • Repeatability.

13. Why Control Groups? • Why did we need to have a group of spiders given just water? Weren’t we testing just caffeine? • Was this a web from a normal spider or a caffeine spider? http://www.trinity.edu/jdunn/spiderdrugs.htm

14. Control Group • The control group is there to be the “normal” result. • It’s the “standard” to which we compare other results. • Without a control, we don’t truly know what normal is. • To identify the control group, simply find the test subjects that are not given any special treatment.

15. Controls and Constants • By the way, don’t forget that controls are different from constants. • Constants are things kept the same in an experiment. Sometimes constants are referred to as “controlled variables.” • Example: All spiders used in the experiment were the same species. • Controls are the test subjects treated “normally.” • Example: Spiders not given any kind of “treatment” like caffeine.

16. Spiders on Drugs • Scientists actually did this test. • NASA scientists! • Here’s what they found: • Normal spiderweb

17. Spiders on Drugs • Caffeine: • Mescaline/peyote:

18. Spiders on Drugs • Marijuana: • Benzedrine/Speed:

19. Spiders on Drugs • Sleeping Pills

20. The first one? • LSD

21. Why do we need a control group? • Another reason we need a control group is because of the placebo effect. • Basically, the placebo effect states that if you give patients a pill (even one that does nothing), but tell them it works, the patient frequently will achieve better health (or at least perceive it). • In other words, “thinking” you’re getting better can actually make you feel better! • It works with pills, (fake) surgery, and even just telling people they’re getting better.

22. The Placebo Effect • To get around the placebo effect, doctors give patients…a placebo! • A placebo, sometimes called a sugar pill, is a pill designed to look like medication but actually do nothing. • The term “placebo” can be used for other things that do nothing but look like they might, as well. • More on the placebo effect: TED – Eric Mead

23. What’s a variable group? • The variable group is where you test your hypothesis. • In the spider example, it’s the caffeinated spiders. • You compare the variable group to the control group. • Example: Comparing the webs of caffeinated spiders to the “control” (normal diet) spiders.

24. One last bit on variables… • There’s actually two kinds of variables out there – dependent variables and independent variables. • Dependent variables (sometimes called responding variables) are those that are measured in the experiment. • In other words: “What you measure.” • Example: Spider web shape.

25. One last bit on variables… • Independent variables are those changed by the experimenter. Typically there’s a general category of independent variables, and they’re often the treatments. • In other words: “What you change.” • Example: Substances given to the spiders. • BIG HINT: The independent variable group is sometimes called the treatment groupor the experimental group. • What’sbeing treated in the experiment? The independent variable.

26. Analyze Your Data • You need to make sure your data are significantly different from chance. • Do enough spiders given caffeine make weirdo webs? • What if some of the caffeine spiders just aren’t good at making webs to begin with, caffeine or not?

27. Draw Your Conclusion • Your conclusion is the grand end result of everything you’ve done and all the evidence you’ve found. • Your conclusion may support your hypothesis or it may not, it doesn’t matter. • What does matter is that your conclusion is supported by your data.

28. Putting It All Together • Scientific Method – Simpsons • Scientific Method – Phineas and Ferb

29. After the Scientific Method • When a group of experiments all seem to be confirming the same pattern, that pattern may be considered a theory. • A theory is a well-tested explanation that explains a wide range of observations. • Basically, a concept that proves a lot of hypotheses. • A theory is not an unproven statement or something scientists just “think” is the case.

30. Theory Examples • Can you think of any theories that exist? • Quantum Theory • Theory of Evolution • Theory of Gravity

31. Reasoning • There are two ways to “reason” according to science: • Deductive reasoning • Inductive reasoning • Neither one is necessarily correct, but they are both different.

32. Deductive Reasoning • Think of it as “big-to-small” reasoning: • Example: • All humans are mortal • Justin Bieber is human • Therefore, Justin Bieber is mortal http://www.socialresearchmethods.net/kb/dedind.php

33. Inductive Reasoning • “Small to big” reasoning: • Example: • Beyoncé lip-synced • Beyoncé is a pop singer • Therefore, other pop singers lip sync

34. Deductive or Inductive? • I like cheese. • Pizza has cheese. • I will like pizza. • This is an example of inductive reasoning. • I start with a specific statement (I like cheese – a component of a larger dish) and move to a general statement that I will like pizza. • Maybe I don’t like tomato sauce. That could be a dealbreaker. But we don’t know that yet…

35. Deductive or Inductive? • I can ice skate. • Hockey involves ice skating. • Therefore, I will be good at ice hockey. • This is also inductive. • I am able to do a small component of a larger picture.

36. Labeling the Experiment • Francisco Redi was one of the first to prove that maggots don’t come from rotting meat. • He used three jars: one open, one covered with netting, and one sealed. • Into each he placed bits of meat and let it rot. • His hypothesis was that maggots come from flies. • Notice that this is a testable hypothesis.

37. Labeling the Experiment • What’s his control? • What’s his independent variable? • What’s his dependent variable? • What are the constants? Flies No flies Jar 1: Jar 2: Jar 3: No flies http://faculty.sdmiramar.edu/dtrubovitz/micro/history/Redi.html

38. Answers • Control • Meat in the open jar (Jar 1). • Independent Variable • Jar coverings. • Dependent Variable • Maggots/flies. • Constants • Same jars, same meat, same location.

39. Labeling the Experiment • A biologist thinks that exercising is good for mice. • He takes 20 two-week-old mice and gives them all identical cages and identical diets, and he keeps them in the same room. • 10 mice also receive an exercise wheel. The other 10 receive an exercise wheel that does not spin. • He records their life spans and compares. • What is the hypothesis? • What is the sample size? • What are the constants? • What is the control (or control group)? • What is the variable (or variable group)? • What’s the independent variable? • What’s the dependent variable? • Could anything have been done better?

40. Answers • Hypothesis • Mice that exercise live longer. • Sample Size • 10 (20 total mice, but in two groups of 10). • Constants • Same age, same room, same cage, same exercise wheels. • Control • Mice with a non-spinny wheel. • Variable/Treatment Group • Mice with a spinny wheel. • Independent Variable • Exercise or no exercise. • Dependent Variable • Life span. • Improvements • Same litter of mice, bigger sample size.

41. Closure: Bad Science? • Bad Science: • TED: Ben Goldacre – Battling Bad Science • Publication Bias: • TED: Ben Goldacre – What Doctors Do Not Know About the Drugs They Prescribe • Science Denial: • TED: Michael Specter – The Danger of Science Denial