Where are we so far?
Our first two days have focussed mainly on the first of three components
of statistical studies:
 Collect data (statistical design)
 Organize data (data analysis)
 Draw conclusions from data (statistical inference)
Here are some highlights:

Many problems with statistical studies are not mathematical.
(7 critical components)
 Most studies "do the math" correctly.

You can't do good statistics unless you start with good data.
 Measuring can be nontrivial (validity, reliability, bias, variability)
 People are complicated (to get data about)

Good samples must be
 representative (use randomization to avoid/reduce bias),
 large enough (to reduce variability)

There are fundamental differences between observational studies and
experiments.
 Cause and effect can never be established on the basis of an observational
study alone.
 By randomly assigning treatments to individuals, experiments can give
strong evidence of cause and effect relationships.
Where to next?
Phase Two (data analysis): What do we do with all this data once we have it?
We will continue to revisit data collection issues as they arrise.
Last Modified:
Thursday, 11Jan2001 16:02:18 EST
Maintained by:
Randall Pruim
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