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Astronomy 103

This guide introduces the principles of science and astronomy, emphasizing the scientific method as a vital process for solving problems and understanding our world. We explore the characteristics that define a good scientific theory, the importance of making accurate predictions, and how scientists must remain open to revising theories in light of new evidence. We also discuss pseudoscience, illustrating the differences between legitimate science and fields like astrology, which lack rigorous experimental backing. A solid grasp of these concepts is essential for anyone studying science.

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Astronomy 103

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  1. Astronomy 103 Janet McLarty-Schroeder

  2. Welcome to Astronomy!

  3. What is a Science?(And why do I have to take one?) Science is a process! It is how we go about finding an answer to a question or solving a problem. Everyone should have a good method of solving problems and have some understanding of the world around them.

  4. Assumptions Rules Model Predictions Measurements Experiments The Scientific Method

  5. Scientific Theories • n A scientific theory is “good” if it: • m Accurately describes a large class of observations with a model that contains only a few arbitrary elements. • m Makes definite, accurate predictions about the results of future observations. • n You can never prove anything. The next observation may contradict some element of the model. • A scientific theory is disproved when a single observation disagrees with the model. Scientists must revise, even scrap, existing theories to accommodate new observations. n A particular scientific theory may not be unique. It must be repeatable!

  6. Pseudoscience A pseudoscience is a body of hypotheses treated as true without a consistent, comprehensive body of experimental evidence. A pseudoscience is identified not by the subject matter, but by its method of treating evidence. Astrology has respectable origins in ancient cosmologies, but its modern implementation is usually for fun or commercial exploitation of the gullible. Its primary failures as a science include (1) predictions that are wrong are not used to improve the model, and (2) the parameters and rules are vaguely defined or just arbitrary.

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