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Chapter 2 Thinking Critically About the Environment

Chapter 2 Thinking Critically About the Environment. Basing our ideas and policies on SOUND SCIENCE, not opinion or conjecture. Sound Science : continual refining of understanding by questioning and active investigations of questions. A Brief History of Scientific Thought.

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Chapter 2 Thinking Critically About the Environment

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  1. Chapter 2 Thinking Critically About the Environment Basing our ideas and policies on SOUND SCIENCE, not opinion or conjecture. Sound Science: continual refining of understanding by questioning and active investigations of questions.

  2. A Brief History of Scientific Thought • Early History: • Ancient Babylonia and Egypt: • -observations carried out to enhance • agriculture, and for religious reasons. • -predictions of human events based • on natural occurrences, such as star • position.

  3. Key: Ancients did not distinguish between science and religion. 2) Greeks: -developed more sound,theoretical approach to science. -knowledge for its own sake. Key: gradual movement of pure science away from religion.

  4. 3) Modern Science: -late 16th, early 17th century -development of scientific method -first described by Francis Bacon in 1620. -Galileo was a big proponent of valid scientific investigation, rather than conjecture. Key: Questions like “How?” increased.

  5. Assumptions of Science • Natural events follow patterns that can be • understood by observation. 2) Basic patterns in nature are the same in all places throughout the universe. 3) Science is based on induction; the extension of observations to generalizations. 4) Generalizations can be tested for validity. 5) Science can never offer absolute proof for any theory, only disproof.

  6. What is PROOF? Deductive vs. Inductive Reasoning Deductive reasoning is based on premises, which are initial assumptions about a subject. If the initial premise is incorrect, the reasoning based on it will be incorrect. Problem: D.R. does not require that the premise be true, only the reasoning.

  7. Inductive reasoning is based on observation, which cannot usually be used with a 100% certainty. Ex: “All swans are white” What we really mean: “All the swans that we have observed were white”. There may indeed BE black swans, but we have not seen any.

  8. A proof in inductive reasoning, therefore, leads to a probability that the proof is valid. This allows us to express our certainty about the conclusion, based on the initial quality of our observations. Problem: this process is often mistaken for deductive reasoning, which leads to misunderstanding of the meaning of science

  9. Measurement and Uncertainty Scientists know that ALL measurements are approximations, limited by the type of instrument used to take the measurement. Uncertainties caused while performing an experiment are called experimental errors. Errors can be systematic, or random

  10. Systematic errors occur consistently, such as when a machine is poorly calibrated. Ex: ALL temperature readings in an experiment are low by 5 degrees C due to a poorly calibrated thermometer. Random errors occur usually once, because of a recording error, or an error in calculation of a single number. Ex: a transcription of 90 to 09

  11. The Methods Of Science -Observation: made through any of the five senses, or by instruments that measure beyond our capability. -an observation that is agreed upon is called a fact. -an inference is an idea based upon an observation, but must first be confirmed.

  12. Example: a white crystalline substance is observed, and an inference is made that the substance is table sugar. Before this inference can be made a fact, the inference must be tested for validity. How could you test this inference?

  13. A hypothesis is a way to test an inference. Generally, a hypothesis is formed into an “ if-then” statement. A hypothesis is held to be true until it is disproved. Therefore, every hypothesis must be able to be tested for validity.

  14. A Proper Experiment For an experiment to properly test a Hypothesis, it has to be a Controlled Experiment. A controlled Experiment has several key components: • A proper Control Group, which serves • as a comparison of change.

  15. 2) An Experimental Group, upon which any changes will be applied. Types of Variables • An Independent Variable is the one • which is applied by the scientist. • (Manipulated Variable) -A Dependent Variable is one which is monitored for change. (Responding Variable)

  16. 3) Replication of Groups -Especially in Biology or Environmental Science, the number of Control and Experimental replicates should be as high as is feasible. -This accounts for natural variability, and allows proper statistical analysis of the data to be taken.

  17. Precision vs. Accuracy Precision is the degree of exactness with which a measurement is made. Ex: a thermometer that measures to .001 degrees is more precise than one that measures to .1 degree Ex: a ruler marked in mm vs. cm

  18. Accuracy is the degree to which measured values are correct, or agree with accepted values. Ex: a watch that is set to the proper time. Precision does not always guarantee accuracy! Ex: a Rolex watch set to the wrong time.

  19. The Need to Define Operational Definitions describe parts of an experiment in a way so that other scientists can understand their meaning. This allows for the experiment to be replicated by others, a key component of valid science.

  20. Ex: common measurement values in recipes. (Cup, tablespoon, etc…) For a valid experiment, the variables (dependent and independent) must be defined before the experiment is carried out. Ex: We will measure the amount on CO2 in the atmosphere in ppm.

  21. Taking Data During an experiment, data must be recorded. Data may be numerical, or quantitative data, or nonnumeric, or qualitative data. Ex: Qualitative: relative sizes (s/m/l), colors, general weather observations Ex: Quantitative: measurements, weather Numbers(inches of rainfall), temperature

  22. Sometimes it is possible to convert qualitative data into quantitative data. This makes it much easier to subject the data to statistical analysis. Ex: levels of plant disease on a crop -visually given a rating of 1-5, with 1 having the least disease. It is VITAL that operational definitions are given for performing this exercise.

  23. Science vs. Technology The terms “science” and “technology” are often interchanged, but this is wrong. Science refers to the understanding of The natural world. Technology refers to the control of the natural world, for the benefit of humans.

  24. Science often leads to new technology, and new technology often leads to new avenues of science, but they are distinct ideas. Science is often limited by the available technology. When the technology matures, the science that uses it will also mature. Ex: telescopes, satellites, Hubble

  25. Objectivity in Science While the goal of science is to be value- free, it is understandable that a scientists social values and ethics will come into play. It is vital that a scientist understand their biases, and try to minimize rather than ignore them.

  26. High standards for evidence are one way of ensuring that objectivity is maintained.

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