Transcript
Science 1101Science 1101
Science, Society, and the Environment IScience, Society, and the Environment I
Instructor Valerie KingInstructor Valerie King
Lecture 1 Outline
I. What is Science? A. Forms of Scientific Inquiry B. Types of Logic
II. Scientific DesignA. Scientific MethodB. Theory and Laws
III. Scientific Method in ActionA. ExamplesB. Statistics
What is Science?
“Science” derived from Latin ‘to know’Way of asking and answering questionsSeeking answers to questions about
natural phenomena (we are therefore limited to what kinds of questions we ask)
Scientific thinking reduces emotional reactions
Forms of Scientific Inquiry
Discovery or Descriptive Science– Observation– Qualitative vs. Quantitative data
Types of Logic
Inductive Reasoning– Derive generalizations based on specific
observations
Types of Logic
Inductive Reasoning– Derive generalizations based on specific
observationsDeductive Reasoning
- Specific predictions follow from general premise
Forms of Scientific Inquiry
Discovery or Descriptive Science– Observation– Qualitative vs. Quantitative data
Hypothesis-Based Science
Scientific Design
Scientific knowledge begins with an observation and a proposed explanation.
Explanation called a hypothesisA hypothesis is testable and falsifiable In science hypotheses are tested by using
them to make predictions about how a particular system will behave
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
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?
Theories and Natural LawsTheory: 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
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 wouldn’t start (observation)
Scientific Method in Action
Example:You got in your car to drive up here and turned the key but the car wouldn’t start (observation)
Hypothesis: There is something wrong with the car
Scientific Method in Action
Example:You got in your car to drive up here and turned the key but the car wouldn’t start (observation)
Hypothesis: There is something wrong with the car
Predictions: battery dead, ignition problem, out of gas
Scientific Method in Action
Test predictions: turn on headlights, check spark plug wires, dip stick in gas tank
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
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
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: King’s collar repels fleasPrediction: dogs wearing the King collar
will have fewer fleas than dogs not wearing the King collar
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.
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.
Let’s recap
Hyp: King’s collar repels fleasPred: dogs wearing King’s collar will have
fewer fleas than those without collarIV: King’s collar DV: presence of fleasCV’s: anything that might effect the number
of fleas on the dogsCan we think of some???
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.
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
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
• 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
Effect of Polar Bear coat color on prey capture
Color of Bear White DarkNumber of Prey 12 7
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
Effect of Polar Bear coat color on prey capture
Color of Bear White DarkMean Number of Prey captured
12 7
Mean: sum the values, divide by the number of values
• 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!
• Assumptions:1. All of the bears are equally hungry2. Spray painting the bears has no effect on their behavior etc. accept to make them stand out on the ice3. Our sample of bears is a good representation of the polar bear population in general
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
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