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  • == Problem 1: Arbitrary Random Variables == Let <math>U</math> be a uniform random variable on [0,1].
    4 KB (596 words) - 12:57, 22 November 2011
  • ...the function is a "non-decreasing function" and that U is a uniform random variable. This is enough information to make this step. So, ...x)) = F(x)\quad \text{(because }\Pr(U \leq y) = y,\text{ since }U\text{ is uniform on the unit interval)}
    862 B (156 words) - 05:42, 21 October 2008
  • ...correct, I forgot the 2pi factor to change the range of the uniform random variable from [0-1] to [1-2pi].
    318 B (57 words) - 16:07, 21 October 2008
  • OK, so what we have initially is a uniform random variable on the interval [0,1]. ...hat an exponential random variable with λ=0.5 is made out of two gaussian random variables with the relationship '''<math>D=X^2+Y^2</math>'''
    1 KB (186 words) - 11:47, 21 October 2008
  • *(a) What is the maximum variance possible for a Bernoulli random variable? *(b) What is the maximum variance possible for a binomial random variable, with parameter <math>n = 1000</math>?
    3 KB (528 words) - 12:58, 22 November 2011
  • The parameter of an exponential random variable has to be estimated from one sample. What is the ML estimator? Is it unbias == Problem 4: Uniform Parameter Estimation ==
    3 KB (500 words) - 12:50, 22 November 2011
  • == Problem 1: Random Point, Revisited== In the following problems, the random point (X , Y) is uniformly distributed on the shaded region shown.
    4 KB (703 words) - 12:58, 22 November 2011
  • *'''I. Guyon and A. Elisseeff, "An Introduction to Variable and Feature Selection", Journal of Machine Learning Research, vol. 3, pp.11 Variable and feature selection have become the focus of much research in areas of ap
    39 KB (5,715 words) - 10:52, 25 April 2008
  • ...{-j\nu}). Use the fact that the sequence was derived from a uniform random variable. The link below (from wikipedia) is useful to get the info you need from th ...ndering if its ok to use randn instead when we want to generate the random variable between -0.5 and 0.5...
    2 KB (258 words) - 00:51, 22 March 2008
  • ...d-inline-policy: -moz-initial;" colspan="2" | Expectation and Variance of Random Variables | align="right" style="padding-right: 1em;" | Binomial random variable with parameters n and p
    3 KB (491 words) - 12:54, 3 March 2015
  • | Random variable | Uniform <math> U(a,b) </math>
    6 KB (851 words) - 15:34, 23 April 2013
  • [[Category:continuous random variable]] [[Category:uniform random variable]]
    2 KB (284 words) - 11:49, 26 March 2013
  • [[Category:continuous random variable]] [[Category:uniform random variable]]
    1 KB (157 words) - 11:59, 26 March 2013
  • [[Category:continuous random variable]] [[Category:uniform random variable]]
    1,022 B (148 words) - 12:00, 26 March 2013
  • ...nal density when the condition is an event B (instead of the event "random variable Y=y").
    3 KB (350 words) - 11:24, 6 March 2013
  • *[[Practice Question uniform random variable mean ECE302S13Boutin|Laroche - Compute the mean]] ...302S13Boutin|Kecheng/li485 - Compute first order moment of Gaussian random variable]]
    2 KB (232 words) - 10:56, 14 April 2013
  • ...{-j\nu}). Use the fact that the sequence was derived from a uniform random variable. The link below (from wikipedia) is useful to get the info you need from th ...ndering if its ok to use randn instead when we want to generate the random variable between -0.5 and 0.5...
    2 KB (264 words) - 08:05, 9 April 2013
  • [[ECE600_F13_rv_definition_mhossain|Previous Topic: Random Variables: Definitions]]<br/> [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]
    15 KB (2,637 words) - 12:11, 21 May 2014
  • ...unctions_of_random_variable_mhossain|Previous Topic: Functions of a Random Variable]]<br/> [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']]
    8 KB (1,474 words) - 12:12, 21 May 2014
  • [[ECE600_F13_notes_mhossain|'''The Comer Lectures on Random Variables and Signals''']] <font size= 3> Topic 16: Conditional Expectation for Two Random Variables</font size>
    4 KB (875 words) - 12:13, 21 May 2014

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