quantitative variable

quantitative variable

A variable that can be measured and reported numerically—usually on a continuum or scale—to reflect a quantity or amount.
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Survival analytical techniques were used to assess agreement of a quantitative variable. J Clin Epidemiol 5 8 : 314-315.
Frequency and percentage were calculated for qualitative variables while mean and standard deviation (SD) were calculated for quantitative variable.
When M is a quantitative variable, the most usual (albeit arbitrary) values are the sample mean (zero, when the model is mean centered) and the points located at one standard deviation below and above the mean.
Many of the quantitative variable have broad overlap between normal patients and glaucoma patients, he says, and though qualitative variables have a higher specificity, some may only be significant when they appear with others.
For example, instead of defining a boolean variable [BMI.sub.[less than or equal to]25] (see Table 4), we take the quantitative variable BMI and generate all the possible evaluative linguistic predications and define fuzzy sets [BMI.sub.ExSm], [BMI.sub.SiSm], [BMI.sub.VeSm], [BMI.sub.Sm], ..., [BMI.sub.VRSm], so that the first column in Table 4 is replaced with Table 5.
The plant is operated quantitative variable, the air volume is 16,000 m3 / h In part D object OP East basement and ground floor F also the decommissioning and dismantling of the entire ventilation installations is provided.
In this study we used categorical and quantitative variables. The quantitative variable is the average salary per pilot, while the categorical variable is the type of airline, for which the airlines in Europe have been classified into three types or groups of airline (the categorical variable).
It uses the vast quantity of available baseball records to teach such matters as descriptive statistics for one quantitative variable, sports betting, probability distribution functions for a discrete random variable, confidence intervals, and streaking.
The categorical factor analysis, usually referred to as item factor analysis (Bock & Gibbons, 2010; Wirth & Edwards, 2007), assumes that observed data originate from a discretization of an underlying quantitative variable. Consider the linear factor model defined in Equation (1).
A simple random sample was used with a confidence level of 95% and a margin of error of 2.7 [+ or -] 23.6cmH2O for MIP, which was a quantitative variable that ensured greater sample size.

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