Data Reliability


Data reliability involves the determination of the extent to which the data sample can address the question. For data samples widely distributed over time, one can raise the issue of the reliability of data taken with older instruments.

Data reliability is an issue when you can not measure a phenomena directly but instead you have to use some tracer.

For example:

What is the best way to measure the extent of urban air pollution?

What is the best way to measure acid rain?

Another good example of the issue of data reliability is evidence for Global Warming:

Issues to raise:

Let's see the data:

Here is some Global Data whose reliability is high. There is no doubt that CO_2 in the atmosphere is increasing and is now at unprecedented levels

Methane concentration from ice core data!

This shows strong exponential growth in the last 100 years or so - consistent with growth in the world's population.

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