enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Quantile - Wikipedia

    en.wikipedia.org/wiki/Quantile

    The rank of the second quartile (same as the median) is 10×(2/4) = 5, which is an integer, while the number of values (10) is an even number, so the average of both the fifth and sixth values is taken—that is (8+10)/2 = 9, though any value from 8 through to 10 could be taken to be the median.

  3. Quantile function - Wikipedia

    en.wikipedia.org/wiki/Quantile_function

    For example, they require the median and 25% and 75% quartiles as in the example above or 5%, 95%, 2.5%, 97.5% levels for other applications such as assessing the statistical significance of an observation whose distribution is known; see the quantile entry.

  4. Distribution of the product of two random variables - Wikipedia

    en.wikipedia.org/wiki/Distribution_of_the...

    The distribution of the product of correlated non-central normal samples was derived by Cui et al. [11] and takes the form of an infinite series of modified Bessel functions of the first kind. Moments of product of correlated central normal samples. For a central normal distribution N(0,1) the moments are

  5. Covariance - Wikipedia

    en.wikipedia.org/wiki/Covariance

    A distinction must be made between (1) the covariance of two random variables, which is a population parameter that can be seen as a property of the joint probability distribution, and (2) the sample covariance, which in addition to serving as a descriptor of the sample, also serves as an estimated value of the population parameter.

  6. Joint probability distribution - Wikipedia

    en.wikipedia.org/wiki/Joint_probability_distribution

    If ρ XY equals +1 or −1, it can be shown that the points in the joint probability distribution that receive positive probability fall exactly along a straight line. Two random variables with nonzero correlation are said to be correlated. Similar to covariance, the correlation is a measure of the linear relationship between random variables.

  7. Odds ratio - Wikipedia

    en.wikipedia.org/wiki/Odds_ratio

    The sample odds ratio n 11 n 00 / n 10 n 01 is easy to calculate, and for moderate and large samples performs well as an estimator of the population odds ratio. When one or more of the cells in the contingency table can have a small value, the sample odds ratio can be biased and exhibit high variance .

  8. One in ten rule - Wikipedia

    en.wikipedia.org/wiki/One_in_ten_rule

    For highly correlated input data the one-in-10 rule (10 observations or labels needed per feature) may not be directly applicable due to the high correlation of the features: For images there is a rule of thumb that per class 1000 examples are needed. [11]

  9. Sample size determination - Wikipedia

    en.wikipedia.org/wiki/Sample_size_determination

    This is the smallest value for which we care about observing a difference. Now, for (1) to reject H 0 with a probability of at least 1 − β when H a is true (i.e. a power of 1 − β), and (2) reject H 0 with probability α when H 0 is true, the following is necessary: If z α is the upper α percentage point of the standard normal ...