Sentence examples for most continuous data from inspiring English sources

Most continuous data were distributed non-normally (Kolmogorov-Smirnov test P < 0.05).

Because most continuous data were skewed (by Kolmogorov-Smirnov test), they were analyzed by using regression analysis and generalized linear models after logarithmic transformation.

Most continuous, unbounded stream data such as data constantly produced from heart beat sensors should be treated differently with respect to importance because up-to-date data may have higher influence than old data.

At each altitude, most of the continuous data presented in this report were sampled from a population which approximated a Gaussian distribution as indicated by the p value derived from the Kolmogorov-Smirnoff statistic (p>0.1) except for GLUT1 glucose transporter expression and insulin concentrations.

Most of the continuous data models are taken from pharmacokinetics, whereas in terms of discrete data models, examples from count data, categorical data, and time-to-event data are used.

For the majority of relevant analyses, results were broadly similar when using categorical measures of lifestyle and deprivation compared to continuous measures, and categorical variables are presented here to present the most complete possible data (continuous data available on request).

Alhough the intra-class correlation coefficient (ICC) is questioned by some authors [ 25], it is the basic measure in most reliability studies involving continuous data (degrees, centimetres, etc).

Even though this method of analysis is considered most suitable for pooling continuous data when results are presented in different units of measurement, the issue with this method of analysis is that pooled estimates can only be interpreted as percent of non-overlap of results of two groups and not in actual change in unit of measurement [ 13].

Interobserver agreement was compared via Pearson's correlation coefficient (r), which was determined as the most appropriate statistical test for continuous data measured by different entities to calculate linear correlation.

However, most established methods focus on missing continuous data (1, 2).

Although a natural measure of the central tendency of a sample of continuous data is its mode (the most probable value), the mean and median are the most popular measures of location due to their simplicity and ease of estimation.