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Common Errors in Statistics (and How to Avoid Them), 4th Edition
book

Common Errors in Statistics (and How to Avoid Them), 4th Edition

by Phillip I. Good, James W. Hardin
July 2012
Intermediate to advanced
352 pages
9h 30m
English
Wiley
Content preview from Common Errors in Statistics (and How to Avoid Them), 4th Edition

DEDUCTION AND INDUCTION

When we determine a p-value as we did in the example above, we apply a set of algebraic methods and deductive logic to deduce the correct value. The deductive process is used to determine the appropriate size of resistor to use in an electric circuit, to determine the date of the next eclipse of the moon, and to establish the identity of the criminal (perhaps from the fact the dog did not bark on the night of the crime). Find the formula, plug in the values, turn the crank and out pops the result (or it does for Sherlock Holmes,6 at least).

When we assert that for a given population a percentage of samples will have a specific composition, this also is a deduction. But when we make an inductive generalization about a population based upon our analysis of a sample, we are on shakier ground. It is one thing to assert that if an observation comes from a normal distribution with mean zero, the probability is one-half that it is positive. It is quite another if, on observing that half the observations in the sample are positive, we assert that half of all the possible observations that might be drawn from that population will be positive also.

Newton’s Law of Gravitation provided an almost exact fit (apart from measurement error) to observed astronomical data for several centuries; consequently, there was general agreement that Newton’s generalization from observation was an accurate description of the real world. Later, as improvements in astronomical measuring ...

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