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We will describe robust statistical techniques as alternatives when data do not fit assumptions required by the standard approaches.
When the data do not fit normal distribution in a group or normal variance between groups, non-parametric tests are used.
However, even under these conditions designed to optimize the role of bystander effects the data do not fit a linear no-threshold model and are still consistent with the notion of a threshold dose for neoplastic transformation in vitro by low LET radiation.
As I look out of my office window onto the streets of London, this does not seem to be a remotely plausible description of the circumstances of the British property market.When the data do not fit the theory, the theory is usually wrong.JOHN GILLIGAN Partner Corporate finance BDO LondonThere are two remedies to address the corrosive effects of tax relief for interest expenses.
The experimental data do not fit well to the zero and parabolic diffusion models.
The cpp is a normalized metric thats help to detect cache overflow (when data do not fit in the cache): the curve of cpp increases significantly.
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But the data don't fit.
If the data don't fit, we tend to assume that it's merely because the illness is presenting atypically rather than that our diagnosis might be wrong or incomplete.
The data don't fit into a coherent model, since they demonstrate that a surgical mutation that has a big effect on APC function has no detectable effect on APC/Axin dynamics.
But as I traveled the land, the data did not fit the framework.
But even when raw data does not fit a normal distribution, there is often a normal distribution lurking within it.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com