The phrase "a true sample of" is correct and usable in written English.
It can be used when referring to an authentic or representative example of something.
Example: "This painting is a true sample of the artist's unique style and technique."
Alternatives: "an accurate representation of" or "a genuine example of".
Asked why Dr. Ivins would submit a true sample of his flask in February but a false one in April, the F.BI. scientists said they could not speculate about his motives.
"Previous studies that have attempted to estimate hearing aid use have relied on industry marketing data or focused on specific groups that don't represent a true sample of the United States population," added Lin, an assistant professor in the Johns Hopkins University School of Medicine and Johns Hopkins Bloomberg School of Public Health.
Considering the vulnerability of the target population, it would have been unethical to build a true sample of children with disability for the calibration of the investigators.
It was obvious, though, from the writings of the cognoscenti, that a true sampling of poutine would require a trip to Montreal.
A variety of observations support the premise that the time-averaged biological populations found on the filters constitute a true sampling of the air microbiota.
To examine the statistical likelihood that the numbers of ESTs in each cluster represent a true sampling of the biological variation between the six libraries, and to compare the results of clustering with microarray results [ 19], cluster data were submitted to the IDEG6 website for analysis [ 20].
Generally, calculating p-values is not relevant, inasmuch as the data do not provide all the features of a true sample and a very large number of observations make any difference significant, which results in a multitude of p-values stuck at 0. Models are validated with separate datasets for learning and testing.
AUPR summarizes the quality of the classification illustrated with the precision-recall curve into a single value, with the maximum of 1. AUPR can be interpreted as the probability of obtaining a True sample when it is randomly drawn from the Positive sample set at any ϵ threshold.
Recent research in psychology suggests that most decision biases are caused by a misalignment between event samples known to the individual and the true sample of events.
Hence, the probability that the last true sample of the vector x ~ ( n ) is in the position t depends directly on the downsampling criteria used at the encoder.
Actually, conditions (11) only hold approximately, so that in (13) we should replace the vector ( overline{mathbf{V}} ) containing true samples of the FT of v with the vector ( tilde{overline{mathbf{V}}} ), denoting an approximation of ( overline{mathbf{V}} ).
