3.1 - Chapter3:Producingdata Sampling Experimentation...

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Chapter 3: Producing data Sampling Experimentation Sampling design and experimental design
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  2 Producing data:  Design of experiments A carefully planned and executed experiment can provide good evidence for causation.
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Obtaining data Beware of drawing conclusions from our own experience or hearsay. Anecdotal evidence is based on haphazardly selected individual cases, which we tend to remember because they are unusual in some way. They also may not be representative of any larger group of cases. Available data are data that were produced in the past for some other purpose but that may help answer a present question inexpensively. The library and the Internet are sources of available data. Government statistical offices are the primary source for demographic, economic, and social data (visit the Fed-Stats site at www.fedstats.gov). Some questions require new data produced specifically to answer them. This leads to designing observational or experimental studies.
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Observational study : Record data on individuals without attempting to influence the responses. We typically cannot prove anything this way due to possible confounding. Experiment : Deliberately impose certain conditions on individuals and record their responses. Influential factors are controlled.
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Some terminologies The individuals on which the experiment is done are called the experimental units . If they are human, we call them subjects . A specific experimental condition applied to the experimental units is called a treatment . Comparative experiments Compare drugs (treatments) on patients (units) Compare fertilizers (treatments) on plots (units)
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The explanatory variables in an experiment are often called factors . Each treatment may be formed by combining a specific value (often called a level ) of each of the factors. Example: A fertilizer may be a combination of three factors: N (nitrogen), P (phosphate) and K (Potassium)
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Design:  How to assign the treatments to the  experimental units (subjects)? Fundamental difficulty: variability among the units; no two units are exactly the same. Different responses may be observed even if the same treatment is assigned to different units.
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1 1 1 1 2 2 2 2 Biased if there is a linear fertility trend.
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1 2 2 1 1 2 2 1
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Suppose we have no knowledge about the fertility trend. A good strategy is to do random assignment.
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3.1 - Chapter3:Producingdata Sampling Experimentation...

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