Analyzing the quality product of a road surfaced based on
some quality measure in either the material itself or compaction
process makes sense and is proven by statistics to have a positive correlation. Typically these correlations
are very precise where the line of best fit can be used to estimate the quality
of the final product. I think these are
very useful in conveying statistical findings to the field personal in the form
of heuristics or “rules of thumbs”. One of these
useful ones is that for every 1% deviation in compaction spec equates to 10%
off the life the road. This rule of
thumb can be used to send home a point to workers that their attention to
quality is magnified in the service life of the final product and this is why
quality in their work means so much. To use
statistics in this manner is a powerful management tool to foster anotomony in employees.
Observational studies
do not establish cause and effect it is a logical fallacy. It can be used to
generate hypothesis that then can be tested to establish cause and effect. This explains that some statistics can fit
these lines of best fit but it is not the major contributing factor to the
final outcome. In other words for
example we all know that “people who eat breakfast are less likely to be obese”
and this can be proven statistically but is that the mechanism that is factoring to obesity? Perhaps people who eat breakfast go to sleep on time and aren’t
snacking and playing video games to the wee hours of the morning? 
No comments:
Post a Comment