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- By definition, we have that the variance of random variable <math>Z</math> is given by <br/>2 KB (333 words) - 13:17, 13 June 2013
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- ; within-class variance : <math>\sigma_W^2 = \omega_0 \sigma_0^2 + \omega_1 \sigma_1^2</math> ; between-class variance : <math>\sigma_B^2 = \omega_0 (\mu_0 - \mu_T)^2 + \omega_1 (\mu_1 - \mu_T)^14 KB (2,253 words) - 11:21, 9 January 2009
- * [[2008/10/02_MA375Fall2008walther]] - Recurrence Relations and sequences, variance and independence10 KB (1,377 words) - 13:49, 20 September 2012
- X(n) is i.i.d Gausian 0 mean with variance <math>\sigma_x^2</math><br/>3 KB (522 words) - 05:45, 16 September 2013
- You can follow the same rules for finding the mean and variance of y.2 KB (292 words) - 05:18, 2 April 2009
- '''Definition of expectation and variance''' and their properties3 KB (525 words) - 12:04, 22 November 2011
- ...r of candy bars you eat before you have all coupons. What are the mean and variance of <math>X</math>? [[5.1 - Chris Cadwallader_ECE302Fall2008sanghavi]] Variance4 KB (656 words) - 11:56, 22 November 2011
- Also, note for geom(p), variance is <math>\frac{1-p}{p^2}</math>. I don't think we can simply add all the v715 B (131 words) - 18:25, 6 October 2008
- This is my little scratchpad for the variance.231 B (48 words) - 09:13, 7 October 2008
- ==Variance==413 B (51 words) - 10:28, 7 October 2008
- ...ndently, with each one being a Gaussian random variable with zero mean and variance of 1. Let <math>D</math> be the square of the (random) distance of the poin3 KB (449 words) - 11:57, 22 November 2011
- ...ys that we need to generate a Gaussian variable, do we assume a mean and a variance?138 B (29 words) - 15:43, 20 October 2008
- == Problem 2: Bounded Variance == *(a) What is the maximum variance possible for a Bernoulli random variable?3 KB (528 words) - 11:58, 22 November 2011
- The problem only asks for the variance of a uniform R.V. on the interval [a,b] Thus using the formula for variance:325 B (62 words) - 12:17, 2 November 2008
- To find the maximum variance of a Bernoulli RV first find the variance equation. ...ual to 0 and find the value of p that results in the largest value for the variance.384 B (69 words) - 12:16, 2 November 2008
- the variance of a binomial random variable:490 B (94 words) - 06:00, 3 November 2008
- After maximizing the variance equation, we get the result as:150 B (26 words) - 17:56, 3 November 2008
- To ensure that the calculated maximum variance is indeed a maximum, and not a minimum, you must take the second derivative306 B (56 words) - 18:53, 3 November 2008
- ...math>f_Y(y)</math> of the random variable <math>Y</math>, and its mean and variance, <math>E[Y]</math>, and <math>Var[Y]</math>. ...h>0 < \alpha < 1/2</math>. Then find the conditional mean and conditional variance of <math>Y</math> given that <math>X = \alpha</math>.4 KB (703 words) - 11:58, 22 November 2011
- ...Both of your variances are wrong, remember that you can't have a negative variance. Use the Var[X] = E[X^2] - (E[X])^2 formula. (Gregory Pajot)1 KB (228 words) - 18:34, 9 December 2008
- a)Does any one know what to do to the variance when multiplied by a number? I know that when added together:408 B (78 words) - 10:10, 8 December 2008
- \\how do you find the variance? -carlos leon-195 B (27 words) - 16:51, 9 December 2008
- ...ormula, and from THAT, the variance should also be the same (also from the variance formula).560 B (111 words) - 10:50, 9 December 2008
- a)Does any one know what to do to the variance when multiplied by a number? I know that when added together:408 B (78 words) - 13:12, 9 December 2008
- *Please correct the posterior variance on page 19 (middle of the page): Assignment for "a" after the line "More sp3 KB (543 words) - 11:55, 12 December 2008
- Given this system and the definition of time variance2 KB (379 words) - 06:00, 10 September 2008
- = Time Invariance? or Time Variance? =1 KB (185 words) - 18:56, 10 September 2008
- == Linearity and Time Variance ==753 B (131 words) - 15:23, 11 September 2008
- == Time Variance ==331 B (57 words) - 12:02, 12 September 2008
- == Time Variance check ==616 B (112 words) - 10:11, 12 September 2008
- An example of time variance is turning on your T.V. to a channel. If you turn it on at 10:01 AM, the f549 B (107 words) - 13:25, 12 September 2008
- ...y Fisher's criterion, which applies exactly to Gaussian classes with equal variance and approximately to other models. Variants like Flexible discriminant anal ...zes the distance between the means of the two classes while minimizing the variance within each class. See Lecture 10 for detailed explanation.31 KB (4,832 words) - 17:13, 22 October 2010
- ...rix with random entries, chosen from a normal distribution with mean zero, variance one and standard deviation one. ...d we assume for the parameters of the distribution of mean? What about the variance?10 KB (1,594 words) - 10:41, 24 March 2008
- The univariate case. The variance is assumed to be known. ...be interpreted as: in making prediction for a single new observation, the variance of the estimate will have two components:10 KB (1,488 words) - 09:16, 20 May 2013
- This function has zero mean, H variance, an n-dimensional density, and is not compactly supported.10 KB (1,607 words) - 07:38, 17 January 2013
- ...in and test the system. We generated N = 10<sup>5</sup> samples. Also, the variance for each feature was the same and the mean of each class feature changed de4 KB (735 words) - 21:49, 8 March 2008
- ...zes the distance between the means of the two classes while minimizing the variance within each class.3 KB (430 words) - 09:40, 24 April 2008
- ...flect the correlation between the axis. The diagonal entries represent the variance along that direction(dimension) itself while the non diagonal entries repre3 KB (528 words) - 07:48, 10 April 2008
- The CRLB is the minimum variance achievable by any unbiased estimator for a parameter. ...mator that is unbiased and achieves the CRLB is referred to as the Minimum Variance Unbiased Estimator(MVUE).6 KB (995 words) - 09:39, 20 May 2013
- ...s which result tend to be fficient in the sense of having low within class variance. Applications are suggested for the problems of non-linear prediction, effi39 KB (5,715 words) - 09:52, 25 April 2008
- 4) Estimate of variance and other parameters is often biased ...certain specially-designed priors, leads naturally to unbiased estimate of variance2 KB (287 words) - 09:39, 20 May 2013
- ...h is the average value of the feature vectors. The second parameter is the variance which measures how much the data is scattered around the mean. If the mean of a normal distribution is zero and the variance is one then it is called standard normal distribution.2 KB (247 words) - 07:32, 10 April 2008
- ...that the autocorrelation function evaluated at the origin is equal to the variance of the sequence. I hope this helps. Good luck.2 KB (258 words) - 23:51, 21 March 2008
- ...zes the distance between the means of the two classes while minimizing the variance within each class. See [[Lecture 10_Old Kiwi]] for detailed explanation.3 KB (475 words) - 17:05, 28 March 2008
- ...y Fisher's criterion, which applies exactly to Gaussian classes with equal variance and approximately to other models. Variants like Flexible discriminant anal418 B (56 words) - 10:23, 25 March 2008
- (This is equal only if variance = 0)5 KB (1,003 words) - 07:40, 17 January 2013
- i.e. small variance in the training data can yield large variations in decision rules obtained.6 KB (806 words) - 07:42, 17 January 2013
- ...ts of a data set. The principal components are random variables of maximal variance constructed from linear combinations of the input features. Equivalently, t657 B (104 words) - 00:45, 17 April 2008
- which is the same as maximizing the between-cluster variance<center><math> S_{Total}=S_{W}+S_{B}</math></center> <center><math> tr(S_ ...the between-class variance is equivalent to minimizing the within-class variance.8 KB (1,244 words) - 07:44, 17 January 2013
- ...es from a spherical Normal distribution with different means but identical variance (and zero covariance). ...ks best for images with clusters that are spherical and that have the same variance.3 KB (528 words) - 13:33, 17 April 2008
- ...d embeds the data points in that subspace in a way that best preserves the variance of the input space (original high-dimensional space). If the input data poi4 KB (593 words) - 11:06, 18 April 2008
