Sentence examples for test for data from inspiring English sources

The EPA and the California Air Resources Board have started gathering other manufacturers' vehicles to test for data manipulation; the German government is also investigating the matter; and South Korea has announced an inquiry.

In this study, nonlinear principal component analysis based on unsupervised support vector machine is introduced and incorporated with a discrete-time prediction model and a hypothesis test for data normalization.

You can test for data bias by using more than one set of data — for example, a loan-application system based on historical data will only perpetuate the biases inherent in that data, which will likely show that members of certain groups in the population have not qualified for loans.

This paper considers the one-sample sign test for data obtained from general ranked set sampling when the number of observations for each rank are not necessarily the same, and proposes a weighted sign test because observations with different ranks are not identically distributed.

Table 5 Results of the robustness test for data mining bias Proxy variable Number of different variable operationalizations in the primary studiesa Hyp.

Baseline demographic characteristics comparing the two groups migraine (+MOH) and migraine (-MOH) were calculated using the chi-square test for larger samples and Fisher's exact for samples less than five categorical data and Mann-Whitney U test for data with skewed distribution and unpaired t-test for data following normal distribution.

The P-values calculated by the Kolmogorov-Smirnov test for data-sets of R SN = 0.1 under both conditions are shown in Table 1.

The comparison of these competitive forecasting models encompasses a number of likelihood testing methods, such as the N-test for data consistency in expected number space, the L-test for data consistency in likelihood-space, and the R-test for relative performance checking of seismicity models (Schorlemmer et al. 2007).

Two group comparisons were performed using unpaired t-test for data with Gaussian distribution and Mann-Whitney test if distribution was not Gaussian.

Comparisons of continuous data were made using student's t-test for data with equal variance or Welch's t-test for those with unequal variance.

Characteristics of subjects between non-CAD and CAD groups or men and women were compared using unpaired Student's t-test (for data that were normally distributed) or the Mann-Whitney U-test (not normally distributed).