Normal distributionIn statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is The parameter is the mean or expectation of the distribution (and also its median and mode), while the parameter is its standard deviation. The variance of the distribution is . A random variable with a Gaussian distribution is said to be normally distributed, and is called a normal deviate.
Continuous uniform distributionIn probability theory and statistics, the continuous uniform distributions or rectangular distributions are a family of symmetric probability distributions. Such a distribution describes an experiment where there is an arbitrary outcome that lies between certain bounds. The bounds are defined by the parameters, and which are the minimum and maximum values. The interval can either be closed (i.e. ) or open (i.e. ). Therefore, the distribution is often abbreviated where stands for uniform distribution.
Probability density functionIn probability theory, a probability density function (PDF), density function, or density of an absolutely continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a relative likelihood that the value of the random variable would be equal to that sample.
Binomial distributionIn probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own Boolean-valued outcome: success (with probability p) or failure (with probability ). A single success/failure experiment is also called a Bernoulli trial or Bernoulli experiment, and a sequence of outcomes is called a Bernoulli process; for a single trial, i.
Congenital heart defectA congenital heart defect (CHD), also known as a congenital heart anomaly, congenital cardiovascular malformation, and congenital heart disease, is a defect in the structure of the heart or great vessels that is present at birth. A congenital heart defect is classed as a cardiovascular disease. Signs and symptoms depend on the specific type of defect. Symptoms can vary from none to life-threatening. When present, symptoms are variable and may include rapid breathing, bluish skin (cyanosis), poor weight gain, and feeling tired.
Ventricular septal defectA ventricular septal defect (VSD) is a defect in the ventricular septum, the wall dividing the left and right ventricles of the heart. The extent of the opening may vary from pin size to complete absence of the ventricular septum, creating one common ventricle. The ventricular septum consists of an inferior muscular and superior membranous portion and is extensively innervated with conducting cardiomyocytes. The membranous portion, which is close to the atrioventricular node, is most commonly affected in adults and older children in the United States.
Sample size determinationSample size determination is the act of choosing the number of observations or replicates to include in a statistical sample. 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.
Mixture distributionIn probability and statistics, a mixture distribution is the probability distribution of a random variable that is derived from a collection of other random variables as follows: first, a random variable is selected by chance from the collection according to given probabilities of selection, and then the value of the selected random variable is realized. The underlying random variables may be random real numbers, or they may be random vectors (each having the same dimension), in which case the mixture distribution is a multivariate distribution.
Log-normal distributionIn probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed. Thus, if the random variable X is log-normally distributed, then Y = ln(X) has a normal distribution. Equivalently, if Y has a normal distribution, then the exponential function of Y, X = exp(Y), has a log-normal distribution. A random variable which is log-normally distributed takes only positive real values.
Acyanotic heart defectAn acyanotic heart defect, is a class of congenital heart defects. In these, blood is shunted (flows) from the left side of the heart to the right side of the heart, most often due to a structural defect (hole) in the interventricular septum. People often retain normal levels of oxyhemoglobin saturation in systemic circulation. This term is outdated, because a person with an acyanotic heart defect may show cyanosis (turn blue due to insufficient oxygen in the blood).
Atrioventricular septal defectAtrioventricular septal defect (AVSD) or atrioventricular canal defect (AVCD), also known as "common atrioventricular canal" or "endocardial cushion defect" (ECD), is characterized by a deficiency of the atrioventricular septum of the heart that creates connections between all four of its chambers. It is a very specific combination of 3 defects: 1) Atrial Septal Defect (ASD), a hole in the wall between the right and left atria; 2) Ventricular Septal Defect (VSD), a hole in the wall between the right and left ventricles; and 3) Abnormalities of the mitral and/or tricuspid valves.
Logistic distributionIn probability theory and statistics, the logistic distribution is a continuous probability distribution. Its cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks. It resembles the normal distribution in shape but has heavier tails (higher kurtosis). The logistic distribution is a special case of the Tukey lambda distribution.
Ceramic engineeringCeramic engineering is the science and technology of creating objects from inorganic, non-metallic materials. This is done either by the action of heat, or at lower temperatures using precipitation reactions from high-purity chemical solutions. The term includes the purification of raw materials, the study and production of the chemical compounds concerned, their formation into components and the study of their structure, composition and properties. Ceramic materials may have a crystalline or partly crystalline structure, with long-range order on atomic scale.
CeramicA ceramic is any of the various hard, brittle, heat-resistant, and corrosion-resistant materials made by shaping and then firing an inorganic, nonmetallic material, such as clay, at a high temperature. Common examples are earthenware, porcelain, and brick. The earliest ceramics made by humans were pottery objects (pots, vessels, or vases) or figurines made from clay, either by itself or mixed with other materials like silica, hardened and sintered in fire.
Powder metallurgyPowder metallurgy (PM) is a term covering a wide range of ways in which materials or components are made from metal powders. PM processes can reduce or eliminate the need for subtractive processes in manufacturing, lowering material losses and reducing the cost of the final product. Powder metallurgy is also used to make unique materials impossible to get from melting or forming in other ways. A very important product of this type is tungsten carbide.
Atrial septal defectAtrial septal defect (ASD) is a congenital heart defect in which blood flows between the atria (upper chambers) of the heart. Some flow is a normal condition both pre-birth and immediately post-birth via the foramen ovale; however, when this does not naturally close after birth it is referred to as a patent (open) foramen ovale (PFO). It is common in patients with a congenital atrial septal aneurysm (ASA). After PFO closure the atria normally are separated by a dividing wall, the interatrial septum.
Weibull distributionIn probability theory and statistics, the Weibull distribution ˈwaɪbʊl is a continuous probability distribution. It models a broad range of random variables, largely in the nature of a time to failure or time between events. Examples are maximum one-day rainfalls and the time a user spends on a web page. The distribution is named after Swedish mathematician Waloddi Weibull, who described it in detail in 1939, although it was first identified by Maurice René Fréchet and first applied by to describe a particle size distribution.
Gumbel distributionIn probability theory and statistics, the Gumbel distribution (also known as the type-I generalized extreme value distribution) is used to model the distribution of the maximum (or the minimum) of a number of samples of various distributions. This distribution might be used to represent the distribution of the maximum level of a river in a particular year if there was a list of maximum values for the past ten years. It is useful in predicting the chance that an extreme earthquake, flood or other natural disaster will occur.
Slip castingSlip casting, or slipcasting, is a ceramic forming technique, and is widely used for shapes that can not easily be formed by other techniques. The technique involves a clay body slip, usually prepared in a blunger, being poured into plaster moulds and allowed to form a layer, the cast, on the internal walls of the mould. It is suited for the consistent and precise shaping of complex shapes. It is the standard shaping technique for sanitaryware, such as toilets and basins, and is commonly used for smaller pieces like figurines and teapots.
Posterior predictive distributionIn Bayesian statistics, the posterior predictive distribution is the distribution of possible unobserved values conditional on the observed values. Given a set of N i.i.d. observations , a new value will be drawn from a distribution that depends on a parameter , where is the parameter space. It may seem tempting to plug in a single best estimate for , but this ignores uncertainty about , and because a source of uncertainty is ignored, the predictive distribution will be too narrow.
