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Although measurements are more reliable than commonsense impressions, measurements can be more or less precise and there is always some measurement error.
Instruments, such as microscopes, can extend our ability to observe and measure.
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Our senses respond to combinations of physical properties, rather than isolated ones. For this reason, they are not good measures of those physical properties.
Sources of measurement error can be examined and quantified.
We can learn about the properties of things through indirect measurement (e.g., water displacement) as well as using powerful tools (microscopes).
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Graphs, visual models, simple algebraic formulas, or quantitative verbal statements can be used to represent inter-relations among variables and to make predictions about one variable from knowledge of others.
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Models can propose unseen entities to explain a pattern of data.
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Hypotheses and data are distinct.
We make stronger arguments for our ideas when they fit a pattern of data rather than simply one observation.
We can clarify our ideas by more precisely stating the conditions under which they are true.
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Good arguments involve getting data that help distinguish between competing explanations.
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