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All the values of x begin at the 15 th decimal, so Excel must take them into account. Before calculating the sum 1 + x , Excel first approximates x as a binary number. If this binary version of x is a simple power of 2, the 15 digit decimal approximation to x is stored in the sum, and the top two examples of the figure indicate recovery of x ...
July 2010) (Learn how and when to remove this message) A truncated mean or trimmed mean is a statistical measure of central tendency , much like the mean and median . It involves the calculation of the mean after discarding given parts of a probability distribution or sample at the high and low end, and typically discarding an equal amount of both.
It says what fraction of the variance of the data is explained by the fitted trend line. It does not relate to the statistical significance of the trend line (see graph); the statistical significance of the trend is determined by its t-statistic. Often, filtering a series increases r 2 while making little difference to the fitted trend.
The first part 0.000 is the format with three decimal places for positive numbers. The second part -0.000 is the format with three decimal places for negative numbers (you probably don't have those, but you cannot skip the negative number part in such formatting strings). The third part 0 is what to display in place of single zeros
Surface plot : In this visualization of the graph of a bivariate function, a surface is plotted to fit a set of data triplets (X, Y, Z), where Z if obtained by the function to be plotted Z=f(X, Y). Usually, the set of X and Y values are equally spaced. Optionally, the plotted values can be color-coded.
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This directly results from the fact that the integrand e −t 2 is an even function (the antiderivative of an even function which is zero at the origin is an odd function and vice versa).
A pseudo-Boolean function: {,} is said to be representable if there exists a graph = (,) with non-negative weights and with source and sink nodes and respectively, and there exists a set of nodes = {, …,} {,} such that, for each tuple of values (, …,) {,} assigned to the variables, (, …,) equals (up to a constant) the value of the flow determined by a minimum cut = (,) of the graph such ...