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Special note concerning the degrees of freedom for the sampling distribution of the difference of two means: In most situations, a conservative, and usually acceptable, approach for determining the required number of degrees of freedom is to let df = min{ n1 1, n2 1 }. This is conservative in the sense that it will give a smaller number of degrees of freedom than other methods, which translates to a larger margin of error. If you choose not to use the conservative approach, there are two cases of interest: (1) the population variances are assumed to be equal; (2) the population variances are not assumed to be equal (the usual case). (1) If we can justify the assumption that the population variances are equal, we can pool our estimates of the population standard deviation. In practice, this is rarely done since the statistical test for equal variances is unreliable. However, if we can make that assumption, then df = n1 + n2 2, and the standard error becomes
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Once your policy-based security scheme is ready, IRM is easily integrated with your existing business processes. Individual users can seal documents manually, or you can have them sealed when checked into a content repository. You can also use the IRM Web service API to seal documents from any application in your enterprise. When integrating IRM with other applications, be wary of giving that application superuser access to sealed content. This will allow your application to read all sealed content so it can run reports, or create a searchable index, however it can also be a security hole if that application is compromised. However, there are several business cases where it is important to unseal the document, extract data, then reseal the document, so this rule is not absolute. For example, many documents are sealed to prevent accidental disclosure, or to ensure that when they are opened, users are viewing the most recent copy. In those cases, there is little harm if a trusted application extracts text or creates a thumbnail of the sealed content. IRM supports heterogeneous environments with multiple types of documents:
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