Theory of probability distributions

Probability integral transform

In probability theory, the probability integral transform (also known as universality of the uniform) relates to the result that data values that are modeled as being random variables from any given continuous distribution can be converted to random variables having a standard uniform distribution. This holds exactly provided that the distribution being used is the true distribution of the random variables; if the distribution is one fitted to the data, the result will hold approximately in large samples. The result is sometimes modified or extended so that the result of the transformation is a standard distribution other than the uniform distribution, such as the exponential distribution. (Wikipedia).

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Integral x^x from 0 to 1

In this video, I evaluate the integrals of x^x and x^(-x) from 0 to 1. Although there is no explicit formula for this integral, I will still evaluate it as a series, and the answer is very pretty! Enjoy!

From playlist Integrals

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Electrical Engineering: Ch 19: Fourier Transform (12 of 45) Find Fourier Transformation: Ex. 3

Visit http://ilectureonline.com for more math and science lectures! In this video I will find the Fourier transform of a double pulse input of amplitude=1 to -1 and width=2 (from -1 to 1) into the frequency domain. Example 3. Next video in this series can be seen at: https://youtu.be/Kn0

From playlist ELECTRICAL ENGINEERING 18: THE FOURIER TRANSFORM

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Electrical Engineering: Ch 19: Fourier Transform (13 of 45) Find Fourier Transformation: Ex. 4

Visit http://ilectureonline.com for more math and science lectures! In this video I will find find the Fourier transform of a single transient pulse input of amplitude=1 and width=0 to infinity into the frequency domain. Example 4. Next video in this series can be seen at: https://youtu.

From playlist ELECTRICAL ENGINEERING 18: THE FOURIER TRANSFORM

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How to integrate exponential expression with u substitution

👉 Learn how to evaluate the integral of a function. The integral, also called antiderivative, of a function, is the reverse process of differentiation. Integral of a function can be evaluated as an indefinite integral or as a definite integral. A definite integral is an integral in which t

From playlist The Integral

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Electrical Engineering: Ch 19: Fourier Transform (2 of 45) What is a Fourier Transform? Math Def

Visit http://ilectureonline.com for more math and science lectures! In this video I will explain the mathematical definition and equation of a Fourier transform. Next video in this series can be seen at: https://youtu.be/yl6RtWp7y4k

From playlist ELECTRICAL ENGINEERING 18: THE FOURIER TRANSFORM

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Calculate the Integral Using Symmetry of Inverse Function, Easier Than Integration By Parts

Instead of directly calculating the integration of logarithm function, we use the symmetric property and calculate the integration of exponential function instead.

From playlist Calculus

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How to find the integral of an exponential function using u sub

👉 Learn how to evaluate the integral of a function. The integral, also called antiderivative, of a function, is the reverse process of differentiation. Integral of a function can be evaluated as an indefinite integral or as a definite integral. A definite integral is an integral in which t

From playlist The Integral

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Integral Transforms Lecture 1: Motivation & Introduction. Oxford Mathematics 2nd Yr Student Lecture

This short course from Sam Howison, all 9 lectures of which we are making available (this is lecture 1), introduces two vital ideas. First, we look at distributions (or generalised functions) and in particular the mathematical representation of a 'point mass' as the Dirac delta function.

From playlist Oxford Mathematics Student Lectures - Integral Transforms

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Laplace Transform of f(t) = sin(2t)

ODEs: Compute the Laplace transform of f(t) = sin(2t). This requires finding an antiderivative of e^ax sin(bx); we note a quick solution based on a partial formula. We verify our answer using the IVP y"+4y=0, y'(0) = 2, y(0)=0. Finally we note the general formulas for sin(at) and cos(

From playlist Differential Equations

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Integral Transforms Lecture 7: The Fourier Transform. Oxford Mathematics 2nd Year Student Lecture

This short course from Sam Howison, all 9 lectures of which we are making available (this is lecture 7), introduces two vital ideas. First, we look at distributions (or generalised functions) and in particular the mathematical representation of a 'point mass' as the Dirac delta function.

From playlist Oxford Mathematics Student Lectures - Integral Transforms

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Stochastic Resetting - CEB T2 2017 - Evans - 1/3

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From playlist 2017 - T2 - Stochastic Dynamics out of Equilibrium - CEB Trimester

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Integral Transforms - Lecture 9: The Fourier Transform in Action. Oxford Maths 2nd Year Lecture

This short course from Sam Howison, all 9 lectures of which we are making available (this is lecture 9), introduces two vital ideas. First, we look at distributions (or generalised functions) and in particular the mathematical representation of a 'point mass' as the Dirac delta function.

From playlist Oxford Mathematics Student Lectures - Integral Transforms

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Lecture 8 | The Fourier Transforms and its Applications

Lecture by Professor Brad Osgood for the Electrical Engineering course, The Fourier Transforms and its Applications (EE 261). Professor Osgood continues lecturing on the general properties of the Fourier Transforms by two paths. First, to develop specific transforms and second, to unders

From playlist Lecture Collection | The Fourier Transforms and Its Applications

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Lecture 10 | The Fourier Transforms and its Applications

Lecture by Professor Brad Osgood for the Electrical Engineering course, The Fourier Transforms and its Applications (EE 261). Professor Osgood introduces the final operation of convolution to the central limit theorem. The Fourier transform is a tool for solving physical problems. In t

From playlist Fourier

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Why is the most common total of two dice 7? A *Very* Deep Look

Created by Arthur Wesley and Jack Samoncik This video is an informal mathematical proof of the central limit theorem, using the sums of an arbitrary number of dice as an example Music: Chapter 1: https://www.youtube.com/watch?v=eFpJRGB32Ss Chapter 2: https://www.youtube.com/watch?v=g1pS0

From playlist Summer of Math Exposition 2 videos

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EE102: Introduction to Signals & Systems, Lecture 5

These lectures are from the EE102, the Stanford course on signals and systems, taught by Stephen Boyd in the spring quarter of 1999. More information is available at https://web.stanford.edu/~boyd/ee102/

From playlist EE102: Introduction to Signals & Systems

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Lecture 14 | The Fourier Transforms and its Applications

Lecture by Professor Brad Osgood for the Electrical Engineering course, The Fourier Transforms and its Applications (EE 261). Professor Osgood continues to lecture on distributions. The Fourier transform is a tool for solving physical problems. In this course the emphasis is on relatin

From playlist Lecture Collection | The Fourier Transforms and Its Applications

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6. Laplace Transform

MIT MIT 6.003 Signals and Systems, Fall 2011 View the complete course: http://ocw.mit.edu/6-003F11 Instructor: Dennis Freeman License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu

From playlist MIT 6.003 Signals and Systems, Fall 2011

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Lecture 11 | The Fourier Transforms and its Applications

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From playlist Lecture Collection | The Fourier Transforms and Its Applications

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How to find the average value of a function with integration

👉 Learn how to find the average value of a function using integration. The average value of a function over an interval is given by the integral of the function over the interval divided by the width of the interval. To find the average value of a function, we first find the integral of t

From playlist The Integral

Related pages

Error function | Random variable | Kolmogorov–Smirnov test | Probability theory | Inverse transform sampling | Continuous uniform distribution | Joint probability distribution | Pushforward measure | Cumulative distribution function | Exponential distribution | P–P plot