Eksempler på brug af Central limit på Engelsk og deres oversættelser til Dansk
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Extensions of the Central Limit Theorem.
Udvidelser af en Central Limit Theorem.The central limit theorem would have still applied.
Central grænse sætningen ville stadig have virket.And that is a neat thing about the central limit theorem.
Og det er det der gør central grænse sætningen speciel.He proved the central limit theorem under fairly general assumptions.
Han viste den centrale grænse sætning under forholdsvis generelle antagelser.Illustration of this Extension of the Central Limit Theorem.
Illustration af denne udvidelse af Central Limit Theorem.But the rigorous proof of the Central Limit Theorem came from the Russian mathematicians.
Which was the basis for the previous illustrations of the Central Limit Theorem.
Der var grundlag for den tidligere illustrationer af Centerlinien Theorem.The Central Limit Theorem(CLT) is a powerful and important result of mathematical analysis.
En Central Limit Theorem(CLT) er et stærkt og vigtigt resultat af matematisk analyse.It was with Laplace's work that the first inklings of the Central Limit Theorem appeared.
Det var med Laplace's arbejde, at den første inklings af Centerlinien Theorem forekom.Although the central limit theorem had recently been discovered, Turing was not aware of this and discovered it independently.
Selv om den centrale grænse sætning for nylig var blevet opdaget, Turing var ikke klar over dette og opdagede det uafhængigt.Pierre Simon de Laplace It was with Laplace's work that the first inklings of the Central Limit Theorem appeared.
Pierre Simon de Laplace Det var med Laplace's arbejde, at den første inklings af Centerlinien Theorem forekom.Illustration of the Central Limit Theorem in Terms of Characteristic Functions Consider the distribution function p(z) 1 if -1/2≤ z≤ +1/2 0 otherwise.
Illustration af Central Limit Theorem i form af karakteristiske funktioner Overveje fordelingen funktion, p(z) 1 hvis -1/2 ≤ z ≤ +1/2 0 ellers.It was Lyapunov's analysis that led to the modern characteristic function approach to the Central Limit Theorem.
Det var Lyapunov-undersøgelse, der førte til den moderne karakteristiske funktion tilgang til Centerlinien Theorem.He wrote on the normal distribution and coined the term"central limit theorem" in 1920 which is now standard usage.
Han skrev om den normale distribution og opfandt udtrykket"central grænse sætning" i 1920 som nu er standard brug.And that's the central limit theorem. And what it tells us is we could start off with any distribution that has a well-defined mean and variance.
Og det er netop den"centrale grænseværdi sætning".. og den viser os, at vi kan starte med en hvilken som helst fordeling, som har et vel-defineret gennemsnit og varians.In particular in two papers published in 1900 and 1901, he proved the central limit theorem using a technique based on characteristic functions.
Især i to papirer offentliggjort i 1900 og 1901, han viste den centrale grænse sætning bruger en teknik baseret på karakteristiske funktioner.Chebyshev Andrei A. Markov Alexander M. Lyapunov It was Lyapunov's analysis that led to the modern characteristic function approach to the Central Limit Theorem.
Chebyshev Andrei A. Markov Alexander M. Lyapunov Det var Lyapunov-undersøgelse, der førte til den moderne karakteristiske funktion tilgang til Centerlinien Theorem.Chebyshev started the project to obtain a rigorous development of the Central Limit Theorem and his students, Andrei A. Markov and Alexander M. Lyapunov.
Chebyshev startet et projekt for at få en grundig udvikling af Central Limit Theorem og hans studerende, Andrei A. Markov og Alexander M. Lyapunov.The Central Limit Theorem then implies that dz has a normal distribution and hence is completely characterized by its mean and standard deviation. The mean or expected value of dz is zero.
Central Limit Theorem derefter indebærer, at dz har en normal fordeling og dermed er helt karakteristisk, gennemsnit og standarddeviation Den gennemsnitlige eller forventede værdi af dz er nul.Turing was elected a fellow of King's College, Cambridge, in 1935 for a dissertation On the Gaussian error function which proved fundamental results on probability theory,namely the central limit theorem.
Turing blev valgt en stipendiemodtager fra King's College, Cambridge, i 1935 for en afhandling om He generalised Lyapunov 's conditions for the central limit theorem, studied generalisations of the law of large numbers, worked on Markov processes and stochastic processes.
Han generelle Lyapunov's betingelser for den centrale grænse sætning, studeret generaliseringer af So let's say I have adiscreet probability distribution function. And I want to be very careful not to make it look anything close to a normal distribution because I want to show you the power of the central limit theorem.
Lad os sige, atvi har en diskret sandsynligheds fordelings funktion. og vi skal sikre os, at Although the above distributions suggests that for an extension of the central limit theorem to apply the sample statistic must be representable as a sum, it should be noted that the maximum function can be represented as the limit of such functions; i.e.
Selv om ovennævnte fordelinger tyder på, at en udvidelse af centerlinien theorem at anvende prøven statistik skal være representable som en sum, skal det bemærkes, at den maksimale funktion kan repræsenteres som en begrænsning af sådanne funktioner, f. eks.Twenty years later Chebyshev published On two theorems concerning probability which gives the basis for applying the theory of probability to statistical data,generalising the central limit theorem of de Moivre and Laplace.
Tyve år senere Chebyshev offentliggjort på to teoremer om sandsynlighed, der giver grundlag for anvendelsen af teorien om sandsynligheden for at statistiske data,generalisere den centrale grænse sætning af The random variable dz represents an accumulation of random influences over the interval dt. The Central Limit Theorem then implies that dz has a normal distribution and hence is completely characterized by its mean and standard deviation.
De tilfældige variable dz udgør en ophobning af tilfældige påvirkninger over intervallet dt. Central Limit Theorem derefter indebærer, at dz har en normal fordeling og dermed er helt karakteristisk, gennemsnit og standarddeviation Den gennemsnitlige eller forventede værdi af dz er nul.But what the central limit theorem them tells us is if we add a bunch of those actions together, assuming that they all have the same distribution, or if we were to take the mean of all of those actions together and if we were to plot the frequency of those means, we do get a normal distribution.
Men det som central grænse sætningen fortæller os, er hvis vi lagde en masse af de funktioner sammen, og antog at de alle havde den samme fordeling, eller hvis vi tog gennemsnittet af alle de funktioner og hvis vi plottede frekvensen af de gennemsnit ind, ville vi få en normal fordeling.The random variable dz represents an accumulation of random influences over the interval dt. The Central Limit Theorem then implies that dz has a normal distribution and hence is completely characterized by its mean and standard deviation. The mean or expected value of dz is zero.
De tilfældige variable dz udgør en ophobning af tilfældige påvirkninger over intervallet dt. Central Limit Theorem derefter indebærer, at dz har en normal fordeling og dermed er helt karakteristisk, gennemsnit og standarddeviation Den gennemsnitlige eller forventede værdi af dz er nul.Illustration of the Central Limit Theorem applet-magic. com Thayer WatkinsSilicon Valley& Tornado AlleyUSA Illustration of the Central Limit Theorem What is illustrated below is the histogram for 2000 repetitions of taking samples of n random variables and computing the sum.
Illustration af Central Limit Theorem San José State University Applet-magic. com Thayer Watkins Silicon Valley& Tornado Alley USA Illustration af Central Limit Theorem Hvad er illustreret nedenfor er histogrammet for 2000 repetions af udtagning af prøver af n tilfældige variabler og databehandling summen.Thus the probability density function for w=z2 is given by P(w) w-1/2 for 0≤w≤0.25 P(w)0 for all other values of w Illustration of this Extension of the Central Limit Theorem Below are shown the histograms for 2000 repetitions of taking samples of n random variables and computing the sum of the squares of a random variable which is uniformly distributed between -0.5 and +0.5.
Dermed sandsynligheden tæthed funktion for w=z2 er givet ved P(w)w-1/2 alle 0≤w≤0.25 P(w) 0 alle andre værdier af w Illustration af denne udvidelse af Central Limit Theorem Nedenfor er vist histogrammer for 2000 gentagelser af udtagning af prøver af n tilfældige variabler og databehandling summen af kvadraterne på en tilfældig variabel, som er ligeligt fordelt mellem -0,5 og +0,5.Extensions of the Central Limit Theorem San José State University applet-magic. com Thayer WatkinsSilicon Valley& Tornado AlleyUSA Extensions of the Central Limit Theorem The Central Limit Theorem The Central Limit Theorem(CLT) is a powerful and important result of mathematical analysis.
Udvidelser af en Central Limit Theorem San José State University Applet-magic. com Thayer Watkins Silicon Valley& Tornado Alley USA Udvidelser af en Central Limit Theorem Central Limit Theorem En Central Limit Theorem(CLT) er et stærkt og vigtigt resultat af matematisk analyse.
