L18.2 The Markov Inequality

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MIT RES.6-012 Introduction to Probability, Spring 2018
Instructor: John Tsitsiklis

License: Creative Commons BY-NC-SA
  1. MIT OpenCourseWare
  2. Markov Inequality
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Комментарии
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amazing explanation. Taaliya bajti rehni chahiye. love u, u r my best friend.

anushkagupta
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Holy moly! That was amazing! Thank you so much!!

evelyntromp
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A very clear explanation with examples in 10 minutes. Thank you!

yagneshbhadiyadra
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Well explained and simple to understand. Thank you!

ekleanthony
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I believe there's a mistake at 9:45. That should be 2, not 1/2.

nefarious
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λεω σαν Ελληνας ακουγεται... και μετα κοιταω κατω στην περιγραφή και βγαινω σωστος :p Ευχαριστούμε!!!

jimmydim
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For exponential distribution isn’t the distribution function P(X<= a) = lambda e ^(-lambda a) = e^(-a)? In which case how is the true value of P(X>=a) also e^(-a)?

testalex
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how did you calculate the expected value of the absolute of x?

davidagyeman-duodu
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I do not understand how it works with small a. for example, if E(X) is 4, and I want the probability that x exceeds 2. according to this formula it is smaller than 4/2 which is 2?! I know that! I even know that the probability is <= 1!

rematlen