Your English writing platform
Discover LudwigExact(2)
The basic principle is to use the nearest correct data when the local data is erroneous.
It is shown that the simultaneous correlation of x, t, y, P data is erroneous but this statement is valid only for "classical" treatment.
Similar(58)
The caveat, of course, is that if the data are erroneous, the closed loop may nevertheless function in the artificial simulation environment because it is partially based on those same data.
Potential outliers can arise due to this latter chance variation, where the data point is correct in nature and is simply more divergent than the majority of the data set, or they can arise due to errors where the value of the data point is erroneous.
Comparing PT with historical data of complications for ST is erroneous and may give a biased picture.
If either the experimental data are wrong or the model is erroneous the error will manifest itself in the values of λeff and αw.
However, the exact incidence for any given year based on this data is likely to be erroneous.
However, extracted data may be erroneous, or could have originated from a malicious source.
Hence, using MLE based model selection criterion in presence of contaminated data may be erroneous.
Moreover, people have accepted a rock-bottom level to date — often 80percentt of marketing data may be erroneous.
Conclusions drawn on the basis of poor quality data can be erroneous.
Write better and faster with AI suggestions while staying true to your unique style.
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