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A common misconception is that the Stern Review applied a zero discount rate. [citation needed] In fact, the Stern review's stochastic projections applied many discount rates reflecting a range of consumption projections, all of them positive, even while it took the rate of time preference to be close to zero. This confusion is prevalent.
A related concept is one part per ten thousand, 1 / 10,000 .The same unit is also (rarely) called a permyriad, literally meaning "for (every) myriad (ten thousand)". [4] [5] If used interchangeably with basis point, the permyriad is potentially confusing because an increase of one basis point to a 10 basis point value is generally understood to mean an increase to 11 basis points; not ...
A method analogous to piece-wise linear approximation but using only arithmetic instead of algebraic equations, uses the multiplication tables in reverse: the square root of a number between 1 and 100 is between 1 and 10, so if we know 25 is a perfect square (5 × 5), and 36 is a perfect square (6 × 6), then the square root of a number greater than or equal to 25 but less than 36, begins with ...
The phrase per mille (from Latin per mīlle 'in each thousand') [1] indicates parts per thousand. [2] The associated symbol is ‰, similar to a per cent sign % but with an extra zero in the divisor.
For the figure that shows high sensitivity and low specificity, there are 3 FN and 8 FP. Using the fact that positive results = true positives (TP) + FP, we get TP = positive results - FP, or TP = 40 - 8 = 32. The number of sick people in the data set is equal to TP + FN, or 32 + 3 = 35. The sensitivity is therefore 32 / 35 = 91.4%.
This measure is often rendered as a percentage, spanning 0 to 100. However, if negative values are factored in, as in cases of debt, the Gini index could exceed 1. Typically, we presuppose a positive mean or total, precluding a Gini coefficient below zero. [24]
The false positive rate is calculated as the ratio between the number of negative events wrongly categorized as positive (false positives) and the total number of actual negative events (regardless of classification). The false positive rate (or "false alarm rate") usually refers to the expectancy of the false positive ratio.
A little algebra shows that the distance between P and M (which is the same as the orthogonal distance between P and the line L) (¯) is equal to the standard deviation of the vector (x 1, x 2, x 3), multiplied by the square root of the number of dimensions of the vector (3 in this case).
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