normal random variable उदाहरण वाक्य

उदाहरण वाक्य

1. The random variables ? " W " " n " are independent and identically distributed normal random variables with expected value zero and variance \ Delta t.
2. Circular symmetric complex normal random variables are used extensively in signal processing, and are sometimes referred to as just "'complex normal "'in signal processing literature.
3. The "'polar method "'( attributed to George Marsaglia, 1964 ) is a pseudo-random number sampling method for generating a pair of independent standard normal random variables.
4. A given data point is assigned a value which is either exactly, or an approximation, to the expectation of the order statistic of the same rank in a sample of standard normal random variables of the same size as the observed data set.
5. Alternatively, since a half-normal distribution is always positive, the one bit it would take to record whether a standard normal random variable were positive ( say, a 1 ) or negative ( say, a 0 ) is no longer necessary.
6. This method of producing a pair of independent standard normal variates by radially projecting a random point on the unit circumference to a distance given by the square root of a chi-square-2 variate is called the polar method for generating a pair of normal random variables,
7. If we wish to test the hypothesis that the population odds ratio equals one, the two-sided p-value is / SE ) } }, where " P " denotes a probability, and " Z " denotes a standard normal random variable.
8. In probability theory, the "'Rice distribution "', "'Rician distribution "'or "'Ricean distribution "'is the probability distribution of the magnitude of a circular bivariate normal random variable with potentially non-zero mean.
9. In math we often "-ize " things when we transform them to a more convenient or easily comparable form ( e . g . " normalizing " a vector so it has unit length, " standardizing " a normal random variable so it has mean 0 and SD 1 ).
10. :Logarithms do a few useful things-they turn multiplicative relationships into additive ones, they turn a log-normal random variable into a normal one, and they take things which are centred about 1 and make them centred about 0, which in some circumstances can make analysis easier ( the first two properties are more useful than the third ).