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In mathematics, a unit vector in a normed vector space is a vector (often a spatial vector) of length 1. A unit vector is often denoted by a lowercase letter with a circumflex, or "hat", as in ^ (pronounced "v-hat"). [2] [1] This is especially common in physics context.
Most frequently, t statistics are used in Student's t-tests, a form of statistical hypothesis testing, and in the computation of certain confidence intervals. The key property of the t statistic is that it is a pivotal quantity – while defined in terms of the sample mean, its sampling distribution does not depend on the population parameters, and thus it can be used regardless of what these ...
The analysis of errors computed using the global positioning system is important for understanding how GPS works, and for knowing what magnitude errors should be expected.
Later on, the text can refer to this equation by its number using syntax like this: As seen in equation ({{EquationNote|1}}), example text... The result looks like this: As seen in equation , example text... The equation number produced by {{EquationNote}} is a link that the user can click to go immediately to the cited equation.
Any non-linear differentiable function, (,), of two variables, and , can be expanded as + +. If we take the variance on both sides and use the formula [11] for the variance of a linear combination of variables (+) = + + (,), then we obtain | | + | | +, where is the standard deviation of the function , is the standard deviation of , is the standard deviation of and = is the ...
The earliest reference to a similar formula appears to be Armstrong (1985, p. 348), where it is called "adjusted MAPE" and is defined without the absolute values in the denominator. It was later discussed, modified, and re-proposed by Flores (1986).
Note that since p>0, (>) as , so with probability converging to one, is finite for large n. Moreover, if p ^ {\displaystyle {\hat {p}}} and q ^ {\displaystyle {\hat {q}}} are estimates of different group rates from independent samples of sizes n and m respectively, then the logarithm of the estimated relative risk p ^ q ^ {\displaystyle ...