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In Excel and Word 95 and prior editions a weak protection algorithm is used that converts a password to a 16-bit verifier and a 16-byte XOR obfuscation array [1] key. [4] Hacking software is now readily available to find a 16-byte key and decrypt the password-protected document. [5] Office 97, 2000, XP and 2003 use RC4 with 40 bits. [4]
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The purpose of password cracking might be to help a user recover a forgotten password (due to the fact that installing an entirely new password would involve System Administration privileges), to gain unauthorized access to a system, or to act as a preventive measure whereby system administrators check for easily crackable passwords. On a file ...
Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.
Some statistical tests, such as the analysis of variance, assume that variances are equal across groups or samples, which can be checked with Bartlett's test. In a Bartlett test, we construct the null and alternative hypothesis. For this purpose several test procedures have been devised.
A p-value less than 0.05 for one or more of these three hypotheses leads to their rejection. As with many other non-parametric methods, the analysis in this method relies on the evaluation of the ranks of the samples in the samples rather than the actual observations. Modifications also allow extending the test to examine more than two factors.
Due to popular demand, the "Don't Give a Sheet" template is now available for purchase on Shopify A bride and groom found an "insane but practical" way to narrow down their wedding invitees.
In statistics, deviance is a goodness-of-fit statistic for a statistical model; it is often used for statistical hypothesis testing.It is a generalization of the idea of using the sum of squares of residuals (SSR) in ordinary least squares to cases where model-fitting is achieved by maximum likelihood.