What is Science?

• Science - the study of the natural world
• Science - A way of knowing about the natural world - science restricts itself to explaining the natural world using natural causes only
• Science - a frequently misunderstood process by which new knowledge is obtained

Science Asks Three Basic Questions

1. What's there?
   The geologist examines rocks in the Grand Canyon, the nuclear physicist bombarding atoms and sees what hapens, the tropical biologist describes a previously undiscovered spider in Costa Rica, the paleontologist digging in promising strata looking for plant fossils, are all seeking to find out, 'What's there?'
2. How does it work?
   A geologist comparing the effects of time on moon rocks to the effects of time on earth rocks, the nuclear physicist observing the behavior of particles, the tropical biologist studies the mating activites of the spider, and the paleontologist studying the reproductive structures of the plant fossils are asking, 'How does it work?'
3. How did it come to be this way?
   Each of these scientists tries to reconstruct the histories of their objects of study. Whether these objects are rocks, elementary particles, tropical organisms, or fossils, scientists are asking, 'How did it come to be this way?'

Science is frequently only presented as the 'Scientific Method.'  While there is nothing wrong with the scientific method, it is not the only means through which science is done.

Introduction to the Scientific Method

• The word 'Science' is derived from the Latin verb meaning 'to know.'
• A process known as the Scientific Method outlines a series of steps for answering questions about the natural world
  • The Scientific process is less structured than most people realize
  • There are no international conspiricies of scientists whose goal is to destroy capitalism or the world economy....

Step 1: Observation and/or asking a question Science occurs when someone is curious about a natual phenomenum and asks questions about it The first scientists only sought to explain the natural world around them (why does it rain, why are days longer in summer than in winter, etc... Step 2: The Hypothesis A hypothesis is a tentative answer or solution to the question or problem at hand using natual means to explain the question A good hypothesis is structured as an 'if-then' statement (i.e. if 'A' happens then 'B' will occur) Hypotheses are general causes or explanations of phenomena Hypotheses reflect past experience with similar questions or situations Multiple hypotheses should be proposed whenever possible Hypotheses must be testable If you cannot disprove it (or at least come up with a way to invalidate the hypothesis), it is not a valid hypothesis Hypotheses can be eliminated but never confirmed with absolute certainty - they can never be proved, only disproved Step 3: Experimental Design Once predictions are made, they can be tested by experiments. If test results contradict predictions, then the hypotheses are called into question and explanations may be sought. Sometimes experiments are conducted incorrectly and are at fault. If the results confirm the predictions, then the hypotheses are considered likely to be correct but might still be wrong and are subject to further testing. The experimental control is a technique for dealing with observational error. This technique uses the contrast between multiple samples (or observations) under differing conditions, to see what varies or what remains the same. Step 4: Data Collection and Interpretation Care must be taken with your experimental data, but after you have collected, you must perform an analysis to see if your data support or refute your hypothesis If the data support your hypothesis, this is helpful, but it does not mean your hypothesis is valid - further experimentation and posible modification of your initial experiments must be done to further support your hypothesis If the data do not support your hypothesis, your hypothesis may be invalid. You should repeat the expriemnts for further varification, but if that is done and the data still refute your hypothesis, then you should revise your hypothesis and then test it

Example: Why do Giraffes have long necks?

• Hypotheses 1 - The Feeding Hypothesis:
  • Giraffes have long necks because the long necks enable them to reach food that is unavailable to others.
  • Giraffes have long necks so that they can better feed on leaves on tall trees that other animals cannot reach
  • This was so logical that it was never tested...until now bwahahahahaha.....
  • Studies were done and they determined that giraffes feed at heights approximately 40 -60% of their height
    • Click here for photo
  • However, some giraffes feed at full height - the breeding males, for example
  • These observations do not support the feeding hypothesis, so this hypothesis has fallen out of favor.  A new hypothesis must be created
• Hypothesis 2: The Mating Combat Ritual (Simmons and Sheepers)
  • Giraffes have long necks because long necks are effective weapons for one male against another during mating.
  • This study was more observational in nature - it was difficult, if not impossible, to experimentally test their hypothesis
  • Does this make it scientifically less sound?
    • Actually, most science is done in this way - observation and inductive thought are often more common than experimentation and deductive thought
    • This does not make it bad science, it just makes it a different way to perform science
  • Assumptions of the hypothesis:
    • Giraffe neck length is variable
      • Zoo studies confirm this
    • Giraffe neck length is heritable
      • They could not do in-depth mating experiments, so it was assumed that this was true
      • This is a logical assumption, since most physical traits related to size are heritable
  • Observations
    • The long neck aids the males in ritualized mating behavior - the males beat each other with their heads in mock combat and to the winner goes the right to mate
      • The ritualized mating behavior was observed in nature (this was the basis of this hypothesis)
      • No other organism does this specific type of combat, but ritualized combat is common among mammals (look at elks and rams)
    • Observations were made - the giraffes with the longer necks were at an advantage in these combats
      • The longer necks allowed the males to generate  more momentum and, therefore, hit harder
      • When you knock a rival down, you get to breed and pass your long-neck genes to your offspring
    • More observations
      • Measurements were done and males have a proportionally longer neck than do females
      • After the body quits growing, the head and neck continue to grow, strengthening the neck and adding thicker bone to the skull
    • Other questions:
      • why do females have longer necks, since they do not need to beat each other up for the privilege of mating?
      • How come giraffe necks do not continue to elongate indefinitely?
      • Was this selection for longer necks to increase mating combat efficiency always present in giraffes or is it a newer evolutionary novelty?
    • The scientists themselves said that this is not the end-all answer and invited other scientists to add to or argue against their finding
  • Awesome video of giraffe mating combat: http://www.youtube.com/watch?v=C7HCIGFdBt8

Theories & Models

• The word 'theory' has a much different usage in science that it typically does in everyday speech
  • Everyday Speech: Theories are one idea that may explain a situation, but frequently there is little to no evidence to support it
  • Science: Theories are robust models which have held up to rigorous testing and observation and allow us to make predictions about the natural world
  • The phrase 'it is just a theory' in reference to a scientific theory does not in any way imply that the theory is unstable, weak, or not supported by most of the scientific community
• Model: A reconstruction of nature for the purpose of study
  • Why make models? Nature can be both very simple and very complex; e.g., although there may be many factors operating, many phenomena can be adequately explained by a much smaller number
  • Models are composed of:
    • Simplification: leaving out complicating factors in order to focus on more fundamental ones
    • Abstraction: one factor represents a host of other ones
    • Sometimes unrealistic assumptions - no friction, completely random mating, etc.
    • A model that included everything would be identical to the real world and just as hard to understand!
  • A model does not necessarily need to be accurate to be useful
    • Light as a particle and light as a wave
    • The Bohr model of the atom

Inductive vs. Deductive Reasoning

• Induction - reasoning from a set of specific observations to form a general conclusion
  • Sherlock has observed the clues from several linked crimes to create a profile of the criminal
    • From this profile, he will be able to predict the criminal's future intentions
    • Are these predictions using inductive or deductive thought?
  • In science, inductive thought is often called 'model building.'
• Deduction - general premises (usually created by induction) are extrapolated to specific examples
• Sherlock uses what he as learned from previous cases to create a possible scenario based upon the specific clues left at the scene of the crime
• Sally used what has previously been studied about the behavior of mice to interpret the behavior of her pet rat

Experimental Design

The specific questions that the experiment is intended to answer must be clearly identified before carrying out the experiment. We should also attempt to identify known or expected sources of variability in the experimental units since one of the main aims of a designed experiment is to reduce the effect of these sources of variability on the answers to questions of interest. That is, we design the experiment in order to improve the precision of our answers.
( Definition taken from Valerie J. Easton and John H. McColl's Statistics Glossary v1.1 )

Control

The problem with this experiment is that the farmer has neglected to control for the effect of the differences in irrigation. This leads to experimental bias , the favoring of certain outcomes over others. To avoid this bias, the farmer should have tested the new fertilizer in identical conditions to the control group, which did not receive the treatment. Without controlling for outside variables, the farmer cannot conclude that it was the effect of the fertilizer, and not the irrigation system, that produced a better yield of crops.

Another type of bias that is most apparent in medical experiments is the placebo effect . Since many patients are confident that a treatment will positively affect them, they react to a control treatment which actually has no physical affect at all, such as a sugar pill. For this reason, it is important to include control, or placebo, groups in medical experiments to evaluate the difference between the placebo effect and the actual effect of the treatment.

The simple existence of placebo groups is sometimes not sufficient for avoiding bias in experiments. If members of the placebo group have any knowledge (or suspicion) that they are not being given an actual treatment, then the effect of the treatment cannot be accurately assessed. For this reason, double-blind experiments are generally preferable. In this case, neither the experimenters nor the subjects are aware of the subjects' group status. This eliminates the possibility that the experimenters will treat the placebo group differently from the treatment group, further reducing experimental bias.

Randomization

• Completely Randomized Design

• Randomized Block Design

Example

A researcher is carrying out a study of the effectiveness of four different skin creams for the treatment of a certain skin disease. He has eighty subjects and plans to divide them into 4 treatment groups of twenty subjects each. Using a randomized block design, the subjects are assessed and put in blocks of four according to how severe their skin condition is; the four most severe cases are the first block, the next four most severe cases are the second block, and so on to the twentieth block. The four members of each block are then randomly assigned, one to each of the four treatment groups.
( Example taken from Valerie J. Easton and John H. McColl's Statistics Glossary v1.1 )

Replication

The above modifed from: http://www.stat.yale.edu/Courses/1997-98/101/expdes.htm

Other Things to Watch For

• If you ever see a study that claims that it was performed at a 'major mid-western university' don’t believe it!
  • Publication is the lifeblood of science - any study worthy of discussion is worthy of citation
• If 'scientists' are ever shown who do not state where they work or from where they got their Ph.D., don’t believe them either!