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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Student Fact Book, Fall 2008, Thirty-Second Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University
Student Fact Book, Fall 2008, Thirty-Second Annual Edition, Wright State University, Office Of Student Information Systems, Wright State University
Wright State University Student Fact Books
The student fact book has general demographic information on all students enrolled at Wright State University for Fall Quarter, 2008.
How Do You Interpret A Confidence Interval?, Paul Savory
How Do You Interpret A Confidence Interval?, Paul Savory
Industrial and Management Systems Engineering: Instructional Materials
A confidence interval (CI) is an interval estimate of a population parameter. Instead of estimating the parameter by a single value, a point estimate, an interval likely to cover the parameter is developed. Many student incorrectly interpret the meaning of a confidence interval. This paper offers a quick overview of how to correctly interpret a confidence interval.
Why Divide By (N-1) For Sample Standard Deviation?, Paul Savory
Why Divide By (N-1) For Sample Standard Deviation?, Paul Savory
Industrial and Management Systems Engineering: Instructional Materials
In statistics, the sample standard deviation is a widely used measure of the variability or dispersion of a data set. The standard deviation of a data set is the square root of its variance. In calculating the sample standard deviation, the divisor is the number of samples in the data set minus one (n-1) rather than n. This often confuses students. This paper offers a quick overview of why the divisor is (n-1) for calculating the sample standard deviation.
The Impact Of Directionality In Predications On Text Mining, Gondy Leroy, Marcelo Fiszman, Thomas C. Rindflesch
The Impact Of Directionality In Predications On Text Mining, Gondy Leroy, Marcelo Fiszman, Thomas C. Rindflesch
CGU Faculty Publications and Research
The number of publications in biomedicine is increasing enormously each year. To help researchers digest the information in these documents, text mining tools are being developed that present co-occurrence relations between concepts. Statistical measures are used to mine interesting subsets of relations. We demonstrate how directionality of these relations affects interestingness. Support and confidence, simple data mining statistics, are used as proxies for interestingness metrics. We first built a test bed of 126,404 directional relations extracted from biomedical abstracts, which we represent as graphs containing a central starting concept and 2 rings of associated relations. We manipulated directionality in four …