Sentence examples for use of numerical data from inspiring English sources

However, the use of numerical data can also be misleading, particularly in attempting to simplify a very complex issue.

Most qualitative researchers who reject the use of numerical data articulate their objections with reference to the philosophical underpinning of their work.

John Snow's use of early epidemiologic tools to associate cholera deaths with water from the Broad Street pump, Louis Pasteur's development of vaccines, and Robert Koch's discovery of tubercle bacillus and the cholera vibro all get their deserved attention; Florence Nightingale's use of numerical data to demonstrate improvements in patient hygiene comes as a pleasant surprise.

Instead of using post-processing of numerical data to enhance signal-to-noise, the paper describes a new EMAT design to increase the magnetic flux density applied to the sample.

Harm was reported or quantified in 135 abstracts [37.2% (CI95%32.2%% to 42.38%)], 40% of them (54 out of 135) used some kind of numerical data: 33 abstracts reported either "p values" (27 articles) or confident intervals (6 articles).

A smart software tool named Support Vector Machine (SVM), which minimizes the upper bound of an empirical risk function, is proposed to approximate the nonlinear function seen in the control law by using very limited number of numerical data.

For the comparison of categorical data, the chi-square test was used, and for the comparison of numerical data, Student's t-test was used.

The Kruskal Wallis test was used to compare independent groups of numerical data (e.g., across tumour stages).

The knowledge about the system is expressed as linguistic fuzzy relationships and the learning schemes of neural networks, capable of learning non-linear mappings of numerical data, are used to train the system.

The CV is a scale-independent measure of the dispersion of a set of numerical data frequently used to evaluate size inequality among individuals in plant populations (Weiner 1995).

Here, we propose an approach to efficiently divide the sampling area for parametric distributions using Fuzzy c-means clustering (FCM) and Centroidal Voronoi Tessellation (CVT) diagrams.FCM has frequently been used in the past for the classification of numerical data.