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The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power .
Particle size analysis, particle size measurement, or simply particle sizing, is the collective name of the technical procedures, or laboratory techniques which determines the size range, and/or the average, or mean size of the particles in a powder or liquid sample. Particle size analysis is part of particle science, and it is generally ...
The sample size is another important concept and can lead to biased data simply due to an unlikely event. A sample size of 10, i.e., polling 10 people, will seldom give valid polling results. Standard deviation and variance are concepts used to quantify the likely relevance of a given sample size.
A textile sample is a piece of cloth or fabric designed to represent a larger whole. A small sample, usually taken from existing fabric, is called a swatch , whilst a larger sample, made as a trial to test print production methods, is called a strike off .
[1] or volume-weighted mean size [2]). It is the mean diameter, which is directly obtained in particle size measurements, where the measured signal is proportional to the volume of the particles. The most prominent examples are laser diffraction [3] and acoustic spectroscopy (Coulter counter). The De Brouckere mean is defined in terms of the ...
Rarefaction curves are created by randomly re-sampling the pool of N samples multiple times and then plotting the average number of species found in each sample (1,2, ... N). N). "Thus rarefaction generates the expected number of species in a small collection of n individuals (or n samples) drawn at random from the large pool of N samples.".
Overabundance of already collected data became an issue only in the "Big Data" era, and the reasons to use undersampling are mainly practical and related to resource costs. Specifically, while one needs a suitably large sample size to draw valid statistical conclusions, the data must be cleaned before it can be used. Cleansing typically ...
It is a major stream in textile engineering, which is under the section of textile chemical processing and applied science. Textile manufacturing covers everything from fiber to apparel; covering with yarn, fabric, fabric dyeing , printing, finishing, garments, or apparel manufacturing.