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In mathematics and statistics, a quantitative variable may be continuous or discrete if it is typically obtained by measuring or counting, respectively. [1] If it can take on two particular real values such that it can also take on all real values between them (including values that are arbitrarily or infinitesimally close together), the variable is continuous in that interval. [2]
Quantitative variables can either be continuous or discrete. Continuous variables capture the idea that measurements can always be made more precisely. While discrete variables have only a finite number of possibilities, such as a count of some outcomes or an age measured in whole years. [50]
Genetic variation can be identified at many levels. Identifying genetic variation is possible from observations of phenotypic variation in either quantitative traits (traits that vary continuously and are coded for by many genes, e.g., leg length in dogs) or discrete traits (traits that fall into discrete categories and are coded for by one or a few genes, e.g., white, pink, or red petal color ...
Hopfield networks [6] [7] are recurrent neural networks with dynamical trajectories converging to fixed point attractor states and described by an energy function.The state of each model neuron is defined by a time-dependent variable , which can be chosen to be either discrete or continuous.
To define probability distributions for the specific case of random variables (so the sample space can be seen as a numeric set), it is common to distinguish between discrete and absolutely continuous random variables. In the discrete case, it is sufficient to specify a probability mass function assigning a probability to each possible outcome ...
This is useful because it puts deterministic variables and random variables in the same formalism. The discrete uniform distribution, where all elements of a finite set are equally likely. This is the theoretical distribution model for a balanced coin, an unbiased die, a casino roulette, or the first card of a well-shuffled deck.
A significant example of directional selection in populations is the fluctuations of light and dark phenotypes in peppered moths in the 1800s. [16] During the industrial revolution, environmental conditions were rapidly changing with the newfound emission of dark, black smoke from factories that would change the color of trees, rocks, and other ...
Furthermore, it covers distributions that are neither discrete nor continuous nor mixtures of the two. An example of such distributions could be a mix of discrete and continuous distributions—for example, a random variable that is 0 with probability 1/2, and takes a random value from a normal distribution with probability 1/2.