Sentences with phrase «bias problem»
The phrase "bias problem" refers to situations where someone's judgment or opinion about something is influenced by their personal beliefs, preferences, or prejudices, rather than being fair and objective. It means their decision or viewpoint is not impartial or unbiased. Full definition
There are three main bias problems with meta - analysis studies.
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It is probably even less reliable than the land station data, even when we consider that the land station data is affected by the urbanization bias problem.
Paradoxically, this means better test alignment could actually make the validity or selection bias problem worse because one no longer offsets the other.
Examples of potential biasing problems in the application of RCS are illustrated by reference to several published studies.
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The recent spate of fake stories inundating Facebook users» news feeds also highlights the AI bias problem.
Based on a series of experiments, [5] simulation studies, [6] and statistical tests, [7] elementary school value - added models do seem to address the selection bias problem well, on average.
When they did this, they discovered some potential instrument bias problems with the recent dataset, which seem to have resulted from the recent transition of the in - situ ocean sounding instruments from the old Expendable Bathythermographs (XBT) system, which has a small warm temperature bias, to the new Argo system, which has a small cold temperature bias in a subset of the instruments.
In the nineteenth century there are exposure bias problems with the NMAT data which are adjusted by comparison with SST, and the SSTs are adjusted using NMAT information.
These new systems overcome the faking, subjectivity, and reference bias problems that plague «first generation» measurement methods.
The urbanization bias problem is a very challenging one.
«The many new tech challenges surrounding the monitoring of old and new sex offenders Main Is there a conflict - of - interest (and a real bias problem) when district judges help define a circuit's sentencing standards?»
LPFI founder Freada Klein says that to fix the bias problem, corporations need to systematically collect anonymous data from employees on their perceptions and experiences.
Plus, the prize has a bias problem: Despite many deserving candidates, only two women have won the physics Nobel.
With this in mind, we decided it was to important to carefully investigate the urbanization bias problem, and check if it had been adequately dealt with.
They have claimed that these adjustments have substantially reduced the urbanization bias problem.
This seems to have convinced many people that the urbanization bias problem is fairly negligible.
As we explained in Section 1, overcoming the urbanization bias problem is not easy.
Changes in microclimate can also lead to non-climatic biases, but these are distinct from the urbanization bias problem.
The various attempts that have so far been made to deal with the urbanization bias problem have been woefully inadequate.
However, before we can discuss our findings, let us first consider in a bit more detail exactly what the urbanization bias problem is...
Interested readers are welcome to read our three papers for a detailed assessment of the urbanization bias problem.
Rather than accurately describing the long and on - going debate which genuinely existed over the urbanization bias problem, the chapter authors ignored or dismissed the papers they personally disagreed with and presented the papers they agreed with (and in some cases had co-authored!)
So, resolving the urbanization bias problem is necessary to address issues such as how the recent warm period compared to the early 20th century warm period.
However the problem is not simple, and the bias problems present a very different challenge to weather station records.
The urbanization bias problem is sometimes incorrectly framed as being a question of whether there has recently been global warming or not.
When Apple debuted its new facial recognition unlock system, Face ID, in September, the company faced questions about how it would sidestep the security and bias problems that have undermined similar facial recognition systems in the past.