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Theory of Probability >> Content Detail



Lecture Notes



Lecture Notes

All Lecture Notes in One File (PDF - 1.9 MB)


LEC #TOPICSNOTES
1Probability spaces, properties of probability(PDF)
2-3Random variables and their properties, expectation(PDF)
4Kolmogorov's theorem about consistent distributions(PDF)
5Laws of large numbers(PDF)
6Bernstein's polynomials, Hausdorff and de Finetti theorems(PDF)
70-1 laws, convergence of random series(PDF)
8

Stopping times, Wald's identity

Markov property, another proof of SLLN

(PDF)
9-10Convergence of laws, selection theorem(PDF)
11Characteristic functions, central limit theorem on the real line(PDF)
12Multivariate normal distributions and central limit theorem(PDF)
13

Lindeberg's central limit theorem

Levy's equivalence theorem, three series theorem

(PDF)
14

Levy's continuity theorem

Levy's equivalence theorem, three series theorem (cont.)

Conditional expectation

(PDF)
15-16

Martingales, Doob's decomposition

Uniform integrability

(PDF)
17Optional stopping, inequalities for Martingales(PDF)
18-19Convergence of Martingales(PDF)
20-21

Convergence on metric spaces, Portmanteau theorem

Lipschitz functions

(PDF)
22Metrics for convergence of laws, empirical measures(PDF)
23Convergence and uniform tightness(PDF)
24-25Strassen's theorem, relationship between metrics(PDF)
26-27Kantorovich-Rubinstein theorem(PDF)
28-29Prekopa-Leindler inequality, entropy and concentration(PDF)
30Stochastic processes, Brownian motion(PDF)
31Donsker invariance principle(PDF)
32-33Empirical process and Kolmogorov's chaining(PDF)
34-35Markov property of Brownian motion, reflection principles(PDF)
36

Laws of Brownian motion at stopping times

Skorohod's imbedding

(PDF)
37Laws of the iterated logarithm(PDF)

 








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