the GOP and repub politicians know full well the facts on both evolution and climate change.. but because both senarios pretty much gaurantee a huge party split, they would rather just use words that discredit scientists (or just blatenly ignore them, like when Bush took condoms off the CDC (center for disease control) website stating there wasnt sufficiant evidence that they protect against anything and that the only true birth control is abstinence. So for the past 7 + years we have been paying millions (well billions) on a program that is outdated by about 50-75 years, science wise… sorry tangent.. any ways.. the point was that using certain words allows for a certain type of control over how people react.. the opposite can be seen since 9/11 and the use of extra aggressive words to create fear, thus allowing the gov to do as it pleases (remember pearl harbor and the US’s isolationism).

I think the point is pretty clear, but as from your response you clearly do not understand you might check the article at The New Scientist.

The IPCC did attach percentage ranges for the verbal expressions in their report. If people only see the verbal expressions in newspaper reports of the study, and not the percentages, this article shows that they come to a different conclusion than was intended by the authors.

For example, when they wrote “very likely” in their report, the authors intended this to mean they thought something was more than 90% likely. However three fourths of readers thought that very likely meant less than 90% and almost half thought this meant less than 66%.

While these are predictions and therefore not matters of certainty, it does make a difference if a study predicts something is more than 90% certain but readers only think they are predicting it is 60% certain. Readers would have an entirely different view of the predictions than was intended by the author. It is far easier to ignore a prediction which they think a scientist is saying has a 60% chance. If they realized the scientist was saying it has over a 90% chance, readers might respond quite differently.

http://www.bioone.org/doi/abs/.....09.59.1.10

Second — and even scientist get this — error bars around a data point are ESTIMATES of uncertainty, and the estimate is only as good as the data and the analysis, and papers and results are challenged all the time on this — it’s the engine of science.  Only a fool would say “yup, this 99% error bar represents 99% certainty of some real aspect of the external independent world.”  No scientist is ever going to say something like that — they know better — and non-scientists’s underestimation basis is probably adaptive in this case.

Consider this paper  in BioScience: “Spurious Certainty: How Ignoring Measurement Error and Environmental Heterogeneity May Contribute to Environmental Controversies .”

Thier point is that error estimates are all over the place — one error estimate out of context tells you nothing. You may find comfortable certainty in such statements as “”Virtually certain” (considered more than 99% likely to be correct),” but good scientists don’t — from the conclusion in their abstract:

Using hierarchical Bayesian techniques, we show how pooling multiple studies can enable us to generate a broader, richer, and more accurate understanding of the dynamics of a system and to better estimate our uncertainties.