Sentence examples for usage of statistical from inspiring English sources

Similarly, recent years have seen the usage of statistical machine learning-based text analysis techniques grow in authorship analysis studies [4],[4],[4],[4]].

Taking this aspect into account, we propose in this section different solutions for the receiver design that depend on the usage of statistical channel knowledge and evaluate the pulse design using the SINR contour as measure.

For the multi-objective cost-efficiency evaluation (IPOG-F, jenny), we followed the same two steps previously mentioned: transformation of the cost-efficiency (two-dimensional) representation into a one-dimensional one and usage of statistical tests, such as the t-test or the nonparametric Wilcoxon test (Signed Rank) (Kohl 2015), to compare each pair of test suites (TTR 1.2 and other).

Therefore, the microsatellites are not homologous and cannot be directly compared, which unfortunately prevents the usage of statistical methods in a meaningful manner.

The problems include optimal design of randomization, the usage of blinding, the calculation of sample size, comparability of baseline information, the clear and definite inclusion and exclusion criteria, the usage of statistical method, the withdrawal and follow-up of patients and the records of adverse events.

By the use of statistical variance analysis, the captured data has been analyzed to investigate the influence on the evaluation through the usage experience of the users.

Fatemieh, Chandra, and Gunter [25] discuss that the usage of a statistical median provides results that are more robust to excessively high or low reports by malicious or deeply faded nodes than when using a mean value.

Furthermore, compared to cross-sectional studies, longitudinal studies have several strengths regarding the interpretation of causal relationships (Kalicki et al. forthcoming), the range of research questions that can be answered and the usage of advanced statistical methods as described in more detail in the following.

Here we highlight the appropriate usage of different statistical tests and demonstrate the value of interactive, univariate (cloud plot), and multivariate (PCA plots) visualization tools for different experimental designs: two-group comparison, meta-analysis, and multigroup comparison.

Gene components, which are synthesized latent factors, and orthogonal transformations of original high-throughput data are interpreted as the projection of high dimensional vector space into a few gene component axes, and the number of gene component (p′) is no longer larger than sample numbers (n), facilitating the usage of classical statistical tools.

The novelty of our method lies in the usage of a variant statistical parameter skewness that shows a difference for any kind of pattern.