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Because actual rather than absolute values of the forecast errors are used in the formula, positive and negative forecast errors can offset each other; as a result, the formula can be used as a measure of the bias in the forecasts. A disadvantage of this measure is that it is undefined whenever a single actual value is zero.
In contrast to the mean absolute percentage error, SMAPE has both a lower and an upper bound. Indeed, the formula above provides a result between 0% and 200%. Indeed, the formula above provides a result between 0% and 200%.
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The Hudson Formula derives from Hudson's Building and Engineering Contracts and is used for the assessment of delay damages in construction claims.. The formula is: (Head Office overheads + profit percentage) ÷ 100 x contract sum ÷ period in weeks x delay in weeks
For example, an experimental uncertainty analysis of an undergraduate physics lab experiment in which a pendulum can estimate the value of the local gravitational acceleration constant g. The relevant equation [1] for an idealized simple pendulum is, approximately,
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 ...
Example [ edit ] If both x {\displaystyle x} and y {\displaystyle y} vectors have cardinal (interval or rational) scale, then without knowing x {\displaystyle x} , the best predictor for an unknown y {\displaystyle y} would be y ¯ {\displaystyle {\bar {y}}} , the arithmetic mean of the y {\displaystyle y} -data.
For a Type I error, it is shown as α (alpha) and is known as the size of the test and is 1 minus the specificity of the test. This quantity is sometimes referred to as the confidence of the test, or the level of significance (LOS) of the test.