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Computational Applied Mathematics Tutorials

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Focus Group: Computational Applied Mathematics

Focus Group: Computational Applied Mathematicsby Lambert Ardy

7 Pages |2171 Views

Multigrid/Multilevel Methods Wavelets Fast Multipole Methods (FMM) Randomized fast algorithms for approximation of Singular Value Decomposition (SV...

History of Computing

History of Computingby Justin Kane

21 Pages|4181 Views

History of Computing People of Egypt, China and ancient Babylonia By 3000 B.C., had developed written symbols to represent numbers Performed simpl...

6.041 / 6.431 4. Counting

6.041 / 6.431 4. Countingby LearnOnline Through OCW

3 Pages |78 Views

The topics covered in this lecture notes are:
• Principles of counting
• Many examples of
–permutations

6.041 / 6.431 1. Probability Models and Axioms

6.041 / 6.431 1. Probability Models and Axiomsby LearnOnline Through OCW

3 Pages|108 Views

This lecture notes introduces Probability Models and Axioms . Probability as a mathematical frame work for reasoning about uncertainty. Topics covered...

6.041 / 6.431 20. Central Limit Theorem

6.041 / 6.431 20. Central Limit Theoremby LearnOnline Through OCW

3 Pages |89 Views

This lecture notes introduces "THE CENTRAL LIMIT THEOREM".
CDF of Zn converges to normal CDF.Various topics covered under this section are Normal...

6.041 / 6.431 25. Classical Statistical Inference - III

6.041 / 6.431 25. Classical Statistical Inference - IIIby LearnOnline Through OCW

3 Pages|70 Views

In this lecture notes we are going to continue with Classical Statistical Inference- III. Here, Review of simple binary hypothesis tests with examp...

6.041 / 6.431  13. Bernoulli Process

6.041 / 6.431 13. Bernoulli Processby LearnOnline Through OCW

3 Pages |143 Views

Various topics covered in this lecture notes are 1. Definition of Bernoulli process 2. Random processes 3. Basic properties of Bernoulli process 4. Di...

6.041 / 6.431 14. Poisson Process - I

6.041 / 6.431 14. Poisson Process - Iby LearnOnline Through OCW

3 Pages|129 Views

In this lecture Review of Bernoulli process has been done and this lecture explores 1. Definition of Poisson Process, 2. Distribution of number of arr...

6.041 / 6.431 15. Poisson Process - II

6.041 / 6.431 15. Poisson Process - IIby LearnOnline Through OCW

3 Pages |134 Views

In this lecture notes we are going to continue withPoisson Process - II. This lesson described the following objectives:
...

6.041 / 6.431 10. Continuous Bayes Rule & Derived distributions

6.041 / 6.431 10. Continuous Bayes Rule & Derived distributionsby LearnOnline Through OCW

3 Pages|110 Views

The tpoics discussed in this Lecture notes are 1.The Bayes variations 2.Continuous counterpart ( Discrete X, Continuous Y and Continuous X, Discrete ...

6.041 / 6.431 2. Conditioning and Bayes

6.041 / 6.431 2. Conditioning and Bayes' Ruleby LearnOnline Through OCW

3 Pages |120 Views

Upon completion of this lesson, you should be able to better understand Conditional probability, Models based on conditional probabilities, Multipl...

6.041 / 6.431 3. Independence of Events

6.041 / 6.431 3. Independence of Eventsby LearnOnline Through OCW

3 Pages|80 Views

This lecture notes introduces Independence of Two Events and Independence of a collection of events. If there are two events A and B occurrence of A ...

6.041 / 6.431 8. Continuous Random Variables

6.041 / 6.431 8. Continuous Random Variablesby LearnOnline Through OCW

3 Pages |75 Views

This lecture notes describes the following Topics:
• Probability density functions
• Cumulative distribution functions ...

6.041 / 6.431 21.Bayesian Statistical Inference - I

6.041 / 6.431 21.Bayesian Statistical Inference - Iby LearnOnline Through OCW

3 Pages|133 Views

“It is the mark of truly educated people to be deeply moved by statistics.” -Oscar Wilde.

This lecture notes introduces Bayesian Statistica...

6.041/6.431 22.Bayesian Statistical Inference - II

6.041/6.431 22.Bayesian Statistical Inference - IIby LearnOnline Through OCW

3 Pages |109 Views

In this lecture notes we are going to continue with Bayesian Statistical Inference - II. Topics covered in this section are (Bayesian) Least Means Squ...

6.041 / 6.431 23. Classical Statistical Inference - I

6.041 / 6.431 23. Classical Statistical Inference - Iby LearnOnline Through OCW

3 Pages|82 Views

This lecture notes introduces Classical Statistical Inference . Various topics covered under this section are:
1. Classical statistics...

6.041/6.431 24. Classical Statistical Inference - II

6.041/6.431 24. Classical Statistical Inference - IIby LearnOnline Through OCW

3 Pages |79 Views

In this lecture notes we are going to continue with Classical Statistical Inference - II. This lesson reviews 1. Maximum likelihood estimation and ...

6.041 / 6.431 7. Multiple Discrete Random Variables

6.041 / 6.431 7. Multiple Discrete Random Variablesby LearnOnline Through OCW

3 Pages|112 Views

In this lecture notes we are going to continue with Multiple Discrete Random Variables and This lesson described the following objectives:

•...

6.041 / 6.431 9. Multiple Continuous Random Variables

6.041 / 6.431 9. Multiple Continuous Random Variablesby LearnOnline Through OCW

3 Pages |97 Views

This lesson reviews PDF(Probability density functions) and introduces Multiple random variables, conditioning and independence.Conditioning is explain...

6.041 / 6.431 16. Markov Chains - I

6.041 / 6.431 16. Markov Chains - Iby LearnOnline Through OCW

3 Pages|106 Views

This lecture notes introduces Markov Chains and various topics discussed under this section are:
• Check out counter example
...

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