Sentence examples for most statistical tools from inspiring English sources

Missing data is a recurrent and very annoying problem, as most statistical tools do not tolerate missing data.

Secondly, the analysis of the complexity of interactions between tree species composition, forest structure, and ecological characteristics of the site claims for the adoption of the most advanced statistical tools (Green et al. 2005).

Removal methods are some of the most common statistical tools for estimating fish abundance in streams and lakes, yet they are prone to produce biased estimates when the assumption of constant capture probability is violated.

These surveys are among the most important statistical tools used by UNICEF and others to identify problems, evaluate programmes and monitor progress towards the Millennium Development Goals.

Statistical classification remains the most useful statistical tool for forensic chemists to assess the relationships between samples.

The most important statistical tool i.e., Chi square error, χ 2 = 4.227 and the efficiency of the method is R 2 = 0.972, where the best results are obtained when these values are close to zero and unity, respectively.

Mann-Kendall's test is a non-parametric method used to test climatological data (Ly et al. 2013; Safari 2012), and studies have shown that it is the most appropriate statistical tool for the analysis of changes in climatological time series or for the detection of abrupt climate change (Klein Tank et al. 2009; Safari 2012).

Because Ancova based on linear model with imbalanced data produced numerous difficulties [28], we used the most appropriate statistical tool, i.e., a mixed model with the following fixed effects: protocol factor, diving, individual factors such as age, weight, etc. and characteristics of the dive profile (e.g., duration of the dive, water temperature, etc).

The chapter also explains analysis bias and introduces some of the most commonly used statistical tools for data analysis.

Survival analysis has become one of the most widely used statistical tools for analyzing clinical research data.

We outline important issues that need to be considered during the planning stage of a study, discuss technical aspects important for obtaining high-quality recordings, provide a brief tutorial regarding the different features that can be measured, and review some of the most frequently used statistical tools used in acoustic analyses.