Presentation on theme: "Today is Friday (!), September 6 th, 2013 Pre-Class: What’s a characteristic of a good experiment? (lots of answers here) P.S. Find your Mythbusters worksheet."— Presentation transcript:
Today is Friday (!), September 6 th, 2013 Pre-Class: What’s a characteristic of a good experiment? (lots of answers here) P.S. Find your Mythbusters worksheet dealies. In This Lesson: Scientific Method (Lesson 2 of 4)
Today’s Agenda Some Inspiration Scientific Method Terminology Defined The Checks Lab Where is this in my book? – P. 5, 8-15
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.
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]
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
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.
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?
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.
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.”
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.
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.
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
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.
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.
Spiders on Drugs Scientists actually did this test. – NASA scientists! Here’s what they found: – Normal spiderweb
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.
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
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.
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.
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 group or the experimental group. – What’s being treated in the experiment? The independent variable.
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?
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.
Putting It All Together Scientific Method – Simpsons Scientific Method – Phineas and Ferb
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.
Theory Examples Can you think of any theories that exist? – Quantum Theory – Theory of Evolution – Theory of Gravity
Reasoning There are two ways to “reason” according to science: – Deductive reasoning – Inductive reasoning Neither one is necessarily correct, but they are both different.
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
Inductive Reasoning “Small to big” reasoning: Example: – Beyoncé lip-synced – Beyoncé is a pop singer – Therefore, other pop singers lip sync
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…
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.
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.
Labeling the Experiment What’s his control? What’s his independent variable? What’s his dependent variable? What are the constants? http://faculty.sdmiramar.edu/dtrubovitz/micro/history/Redi.html Jar 1: Jar 2:Jar 3: FliesNo flies
Answers Control – Meat in the open jar (Jar 1). Independent Variable – Jar coverings. Dependent Variable – Maggots/flies. Constants – Same jars, same meat, same location.
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?
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.
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