Transcript Examining Scientific Claims PowerPoint

Investigating Scientific Claims
Outline
I. Experimental vs. Observational Science
II. Evidence vs. Inference
A. Definitions
B. Examples
III. Types of Errors
A. Random
B. Systematic
IV. Critical Thinking
A. Definition
B. Methods
Experimental vs. Observational
Science
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Experimental: based on direct manipulation
of the independent variables. (polar bear
example from last week)
Observational: based on selecting existing
cases with different values for the independent
variables. E.g. thalidomide babies from the
fifties-look at adults, those whose mom’s took
vs. didn’t take
Historical investigations must be observational
Current investigations may be either
Evidence
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Must be a fact or measurement about
something that has actually occurred
Information attributed to an identified scientific
source
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Specific scientist
Scientific organization
Scientific journal
Examples of Evidence
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Skelly (1997) found that in the presence of
predators, tadpoles (Pseudacris spp.) were
less than half as active as control tadpoles (no
predator present).
Skelly (1997) also found growth rates of more
stationary tadpoles dropped
Smith et. al. found a decline in a Brazilian bird
species
Smith et. al. also found 30% of Brazilian
rainforest has declined
Inference
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Interpretation of data
Conclusion made based on the given facts but
not specifically tested
Examples of Inference
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Taken together, the results of Skelly’s (1997)
experiments suggest Pseudacris spp. tadpoles
have a behavioral trade-off between growth
and risk of predation
Decrease in Brazilian bird species is due to
rain forest decline
Types of Errors
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Random Error: errors in measurement that
vary randomly from one measurement to the
next.
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May be due to person making the measurement
May be due to variations in the equipment
Systematic Error: errors that have a consistent
bias
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May be due to mistakes in setting up or making the
measurement
Equipment not calibrated properly
Minimizing Error
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Random error may be minimized by making
many measurements and averaging the results
Systematic error can NOT be minimized by
increasing #of measurements or by averaging
measurements
Critical Thinking
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Actively and skillfully evaluating information
gathered from observation and experience and
using that insight to form conclusions that
guide your beliefs and actions
Self-directed, self-disciplined, self-monitored,
and self-corrective thinking
Methods of Critical Thinking
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Identify and evaluate premises and
conclusions in an argument
Analyze inferences based on evidence, those
based on value judgments
Assign weight to opposing viewpoints based on
chains of reasoning, sources of information
(reliability)
Adjust weighting depending on relevance to
central issue, lack of specific evidence or
contradictions
Rules for conditionally
accepting a claim
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Conditionally accept claim if it is well supported
by evidence cited in article
Claim is published in reputable journal, work
done by reputable scientists
No evidence in article has contradicted claim
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Do not accept if there is insufficient evidence
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