Not exact matches
With the general
lack of
precise, granular audience measurement
data, media buying brands, agencies, and media outlets hedge their bets when it comes to advertising spend.
Bruce Lanphear, a professor for Faculty of Health Sciences at Simon Fraser University in British Columbia, said the
lack of
precise data presents «a huge problem.»
As the Canadian government scientists note in the Fisheries Oceanography paper: «The 2010 phenomenal run... may forever remain an enigma due to the
lack of
precise ecological and chemical
data.»
However, the fact that we find very «
precise zeros» — that is, we don't find statistically significant relationships even though we have the statistical power in our
data to detect even very modest relationships — implies that neither measurement error nor a
lack of sufficient variation are what's driving our inability to detect a relationship between teaching and research quality.
Lacking that
precise data, all we can do is estimate a range, based on the evidence.
It is maddeningly difficult to track down an exact figure for the pre-industrial global temperature, partially because of a
lack of
precise data, partially because of politics, and partially because of the impenetrability of scientific writing.
NRT
data lack the
precise orbit determination of the standard
data, and often
lack the atmospheric corrections.
Similarly to weather forecasting, efforts can be made to setup a model to match initial conditions at a certain point in time but they are likely to break down pretty quickly because we
lack the quantity and quality of
data to be
precise enough in the setup (and possibly because the chosen model does not accurately produce variability similar to that observed on Earth).