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I will pay for the following essay You can choose one of these topics: The normal distribution and physics, Music and Fourier Series, The volume of the unit ball in n dimensions, Geometric Constructio
I will pay for the following essay You can choose one of these topics: The normal distribution and physics, Music and Fourier Series, The volume of the unit ball in n dimensions, Geometric Constructions in Number theory, Applications of the divergence of the harmonic series, Elimination an. The essay is to be 7 pages with three to five sources, with in-text citations and a reference page.
Normal distribution was mainly advanced as an approximation to the binomial distribution (Roe, 234-256). The utility of the normal distribution is appreciated to be having amazing property of the physical processes that are random variables, which are utilized to safely approximate the normal distribution. Random variation within the natural processes mostly follows the probability distribution and it is referred as the Gaussian distribution in physics and the bell curve within the social science. The main function of describing the normal distribution has a relatively longer tradition in mathematics and physics. De Moivre utilized it in the approximation of the binomial distribution Laplace utilized it in measurement of errors and Gauss utilized it in the analysis of the astronomical data. Normal distribution and physics used in the computation of errors.
Gaussian model is normally represented by the Central Limit Theorem. Central Limit Theorem states that appropriate linear combinations of suitably behaved random variables will be asymptotically shaped thus displaying Gaussian distribution regardless of the underlying distributions of the individual random that are being combined (Benenson et al, 123-167) . Moreover, random variable is normally produced by prevailing linearly combining massive well behaved random variables that are applicable in physics. This is can also be verified by binomial distribution that limit the approximated Gaussian distribution in regard to the discrete random variables. Normal distributions possess numerous convenient properties of random variables with underlying unknown distributions and they all assume the application of normal distribution in physics and astronomy (Roe, 234-256). Approximation normally takes the form of central limit theorem by displaying that the mean of any prevailing variates with any corresponding distribution possess finite mean and variance that normally tends to be the normal
