Science 1101

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Science 1101

• Science, Society, and the Environment I
• Instructor Valerie King

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Lecture 1 Outline

• I. What is Science?
• A. Forms of Scientific Inquiry
• B. Types of Logic
• II. Scientific Design
• A. Scientific Method
• B. Theory and Laws
• III. Scientific Method in Action
• A. Examples
• B. Statistics

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What is Science?

• Science derived from Latin to know
• Way of asking and answering questions
• Seeking answers to questions about natural
  phenomena (we are therefore limited to what kinds
  of questions we ask)
• Scientific thinking reduces emotional reactions

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Forms of Scientific Inquiry

• Discovery or Descriptive Science
• Observation
• Qualitative vs. Quantitative data

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Types of Logic

• Inductive Reasoning
• Derive generalizations based on specific
  observations

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Types of Logic

• Inductive Reasoning
• Derive generalizations based on specific
  observations
• Deductive Reasoning
• - Specific predictions follow from general
  premise

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Forms of Scientific Inquiry

• Discovery or Descriptive Science
• Observation
• Qualitative vs. Quantitative data
• Hypothesis-Based Science

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Scientific Design

• Scientific knowledge begins with an observation
  and a proposed explanation.
• Explanation called a hypothesis
• A hypothesis is testable and falsifiable
• In science hypotheses are tested by using them to
  make predictions about how a particular system
  will behave

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Example

• Hypothesis all objects fall when dropped
• Test this by dropping objects
• Each object we drop is a test of our prediction,
  the more successful tests the more confidence in
  our hypothesis

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• What if we drop a helium balloon?
• What if we drop something in the space shuttle in
  space?
• These are clear exceptions to our original
  hypothesis-does this make our hypothesis invalid?

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Theories and Natural Laws

• Theory a description of the world that covers a
  relatively large number of phenomena and has met
  many observational and experimental tests
• Law of Nature theory (or group of theories)
  that has been tested extensively and seems to
  apply everywhere in the universe-they become part
  of the conceptual framework of a particular field

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Scientific Method in Action

• We use the scientific method in everyday life
• Example
• You got in your car to drive up here and turned
  the key but the car wouldnt start (observation)

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Scientific Method in Action

• Example
• You got in your car to drive up here and turned
  the key but the car wouldnt start (observation)
• Hypothesis There is something wrong with the
  car

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Scientific Method in Action

• Example
• You got in your car to drive up here and turned
  the key but the car wouldnt start (observation)
• Hypothesis There is something wrong with the
  car
• Predictions battery dead, ignition problem,
• out of gas

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Scientific Method in Action

• Test predictions turn on headlights, check
  spark plug wires, dip stick in gas tank

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Scientific Method in Action

• Test predictions turn on headlights, check
  spark plug wires, dip stick in gas tank
• Analyze results headlights work, strong
  ignition spark, no gas on dip stick-gas gauge
  reads half full

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Scientific Method in Action

• Test predictions turn on headlights, check
  spark plug wires, dip stick in gas tank
• Analyze results headlights work, strong ignition
  spark, no gas on dip stick-gas gauge reads half
  full
• Draw conclusion gauge inaccurate, out of gas

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Scientific Method in Action

• I want to market a new flea collar for dogs that
  is a natural remedy-no harsh chemicals. But first
  I have to see if it really works.
• Hypothesis Kings collar repels fleas
• Prediction dogs wearing the King collar will
  have fewer fleas than dogs not wearing the King
  collar

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• Important terms
• Independent (manipulated) variable condition or
  event under study (choose 1)
• Dependent (responding) variable condition that
  could change under the influence of the
  independent variable (measure this)
• Controlled variables conditions which could
  effect the outcome of the expt so they must be
  held constant between groups.

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• experimental group group(s) subjected to the
  independent variable
• control group group not subjected to the
  independent variable, used as measuring stick
• reproducibility producing the same result
  consistently to verify result. It is therefore
  important to describe your experimental design in
  enough detail for others to perform the same
  experiment.

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Lets recap

• Hyp Kings collar repels fleas
• Pred dogs wearing Kings collar will have fewer
  fleas than those without collar
• IV Kings collar DV presence of fleas
• CVs anything that might effect the number of
  fleas on the dogs
• Can we think of some???

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Experimental Design

• Obtain 500 dogs of various breeds from local
  shelters. Have vet weed out the 200 dogs with
  the most fleas. Randomly assign individuals to 2
  groups.
• Board the dogs in identical environments and
  treat them the same except that one group gets to
  wear the King collar and the other group does not
• After 2 wks. The dogs are examined by a vet for
  fleas.

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• Results the dogs wearing the King collars were
  virtually free of fleas after the 2 wk period
  compared to the dogs without the collars which
  had about the same number of fleas as when the
  experiment began

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Second Example

• Observation polar bears are white, you wonder
  why this is so
• Hypotheses
• Match arctic landscape for
  protection/predation
• White fur may reduce heat loss in warm-blooded
  animals
• Maybe polar bears are unable to produce
  melanin therefore they are white as result

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• Prediction polar bears which are white will
  capture more prey than those which are dark
• IV color of bears
• DV number of prey
• Experimental Design spray paint 5 polar bears
  dark(experimental Group)/leave 5 white(control
  group) Track prey capture for 8 weeks

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Effect of Polar Bear coat color on prey capture
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Probability and Statistics

• Probability an attempt to measure and predict
  the likelihood of an event
• Statistics allow you to evaluate comparisons
  between experimental and control groups

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Effect of Polar Bear coat color on prey capture
Mean sum the values, divide by the number of
values
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• Assumptions factors thought to be true for the
  investigation but have not been verified or
  controlled
• Commonly accepted information
• Thought to be held constant but not controlled
• Factors beyond the investigators control because
  of technical or time considerations
• Incorrect assumptions invalidate an experiment!

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• Assumptions
• 1. All of the bears are equally hungry
• 2. Spray painting the bears has no effect on
  their behavior etc. accept to make them stand out
  on the ice
• 3. Our sample of bears is a good representation
  of the polar bear population in general

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Statistics

• Sample Size of observations necessary to have
  a reliable representation of a population
• Confidence Limits estimates that reflect the
  reliability of your mean (average)
• Probability your sample is similar to other
  random samples of that population