biased sampling - traducción al ruso
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biased sampling - traducción al ruso

THE CONSTANT OFFSET OF AN EXPONENT'S VALUE
Biased exponent; Characteristic (biased exponent)

biased sampling      
необъективный [пристрастный] выбор
biased sample         
  • access-date=2008-07-05}}</ref>
  • Simple pedigree example of sampling bias
BIAS IN WHICH A SAMPLE IS COLLECTED IN SUCH A WAY THAT SOME MEMBERS OF THE INTENDED POPULATION ARE LESS LIKELY TO BE INCLUDED THAN OTHERS
Logical fallacy/Biased sample; Spotlight (logical fallacy); Spotlight fallacy; Ascertainment bias; Sample bias; Biased samples; Sample selection bias; Biased sample; Non-random sampling; Spotlight bias; Bias the sample; Unbiased sample; Exclusion bias; Collection bias; Collecting bias; Preservational bias; Self-selection (labor economics)

общая лексика

смещённая выборка

смещенная выборка

biased sample         
  • access-date=2008-07-05}}</ref>
  • Simple pedigree example of sampling bias
BIAS IN WHICH A SAMPLE IS COLLECTED IN SUCH A WAY THAT SOME MEMBERS OF THE INTENDED POPULATION ARE LESS LIKELY TO BE INCLUDED THAN OTHERS
Logical fallacy/Biased sample; Spotlight (logical fallacy); Spotlight fallacy; Ascertainment bias; Sample bias; Biased samples; Sample selection bias; Biased sample; Non-random sampling; Spotlight bias; Bias the sample; Unbiased sample; Exclusion bias; Collection bias; Collecting bias; Preservational bias; Self-selection (labor economics)
смещённая выборка; необъективная [пристрастная] выборка

Definición

Nyquist Theorem
<communications> A theorem stating that when an analogue waveform is digitised, only the frequencies in the waveform below half the sampling frequency will be recorded. In order to reconstruct (interpolate) a signal from a sequence of samples, sufficient samples must be recorded to capture the peaks and troughs of the original waveform. If a waveform is sampled at less than twice its frequency the reconstructed waveform will effectively contribute only noise. This phenomenon is called "aliasing" (the high frequencies are "under an alias"). This is why the best digital audio is sampled at 44,000 Hz - twice the average upper limit of human hearing. The Nyquist Theorem is not specific to digitised signals (represented by discrete amplitude levels) but applies to any sampled signal (represented by discrete time values), not just sound. {Nyquist (http://geocities.com/bioelectrochemistry/nyquist.htm)} (the man, somewhat inaccurate). (2003-10-21)

Wikipedia

Exponent bias

In IEEE 754 floating-point numbers, the exponent is biased in the engineering sense of the word – the value stored is offset from the actual value by the exponent bias, also called a biased exponent. Biasing is done because exponents have to be signed values in order to be able to represent both tiny and huge values, but two's complement, the usual representation for signed values, would make comparison harder.

To solve this problem the exponent is stored as an unsigned value which is suitable for comparison, and when being interpreted it is converted into an exponent within a signed range by subtracting the bias.

By arranging the fields such that the sign bit takes the most significant bit position, the biased exponent takes the middle position, then the significand will be the least significant bits and the resulting value will be ordered properly. This is the case whether or not it is interpreted as a floating-point or integer value. The purpose of this is to enable high speed comparisons between floating-point numbers using fixed-point hardware.

To calculate the bias for an arbitrarily sized floating-point number apply the formula 2k−1 − 1 where k is the number of bits in the exponent.

When interpreting the floating-point number, the bias is subtracted to retrieve the actual exponent.

  • For a single-precision number, the exponent is stored in the range 1 .. 254 (0 and 255 have special meanings), and is interpreted by subtracting the bias for an 8-bit exponent (127) to get an exponent value in the range −126 .. +127.
  • For a double-precision number, the exponent is stored in the range 1 .. 2046 (0 and 2047 have special meanings), and is interpreted by subtracting the bias for an 11-bit exponent (1023) to get an exponent value in the range −1022 .. +1023.
  • For a quad-precision number, the exponent is stored in the range 1 .. 32766 (0 and 32767 have special meanings), and is interpreted by subtracting the bias for a 15-bit exponent (16383) to get an exponent value in the range −16382 .. +16383.
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