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Intellectual property is the term used to describe the legal rights protecting creative works, inventions and commercial goodwill. Intellectual property rights are used to discourage the theft or use without permission of a particular creative work while providing the legal support for different business models to be developed around intellectual property assets. This is based on the principle that the individual who has made an intellectual effort to create an asset must be able to benefit from this effort. This principle also applies, in an equivalent manner, to an individual who has made a manual effort physically to create an asset. IP rights protect the large investments made by music studios, movie studios and the entertainment industry in general and help to create a cycle of revenues that would support new and improved materials while providing profits to shareholders. Even without the use of DRM technology, content owners have the valid expectation that they would benefit

of determining these averages, the method or methods used are also critical in evaluation of molecular mass results.

and afternoon, as needed. Some patients have reported to me that taking it at bedtime keeps them from falling asleep. Occasionally I will prescribe amitriptyline or nortriptyline to be taken prior to bed in combination with desipramine to be taken in the morning and afternoon. The bene cial effects from taking TCAs typically occur within 3 days.33 When prescribing a TCA, it is strongly recommended that the side effects be reviewed with the patient. These medications are associated with many side effects (listed in most medication manuals) that can have a profound effect on patients. I prescribe TCAs for TMD, neck, and headache pain and studies support their effectiveness for these disorders.26,29,34 I generally do not prescribe these until I nd that nonpharmaceutical interventions have not provided satisfactory relief.

Predictive model (or prediction model) See mathematical model Predictor A descriptor variable that is used to build a prediction model p-value A p-value is the probability of obtaining a result at least as extreme as the null hypothesis Range The difference between the highest and the lowest value Ratio scale A scale where the order of the values and the differences between values has meaning and the zero point is nonarbitrary Regression trees A decision tree used to predict a continuous variable Residual The difference between the actual data point and the predicted data point Response variable A variable that will be predicted using a model r-squared A measure that indicates how well a model predicts Sample A set of data selected from the population Sampling error Error resulting from the collection of different random samples Sampling distribution Distribution of sample means Scatterplot.

A graph showing two variables where the points on the graph correspond to the values Segmentation The process where a data set is divided into separate data tables, each sharing some common characteristic Sensitivity Re ects the number of correctly assigned positive values Similarity Refers to the degree two observations share common or close characteristics Simple linear regression A regression equation with a single descriptor variable mapping to a single response variable Simple nonlinear regression A regression equation with a single descriptor variable mapping to a single response variable where whenever the descriptor variable increases, the change in the response variable is not proportionate Simple regression A regression model involving a single descriptor variable Single linkage Minimum distance between an observation in one cluster and an observation in another Skewness For a particular variable, skewness is a measure of the lack of symmetry Slope.

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Within a simple linear regression equation, the slope re ects the gradient of the straight line Speci city Re ects the number of correctly assigned negative values Splitting criteria Splitting criteria are used within decision trees and describe the variable and condition in which the split occurred Spreadsheet A software program to display and manipulate tabular data Standard deviation A commonly used measure that de nes the variation in a data set Standard error of the mean Standard deviation of the means from a set of samples Standard error of the proportion Standard deviation of proportions from a set of samples Statistics Numeric information calculated on sample data Subject matter expert An expert on the subject of the area on which the data analysis or mining exercise is focused Subset A portion of the data..

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Let Y = {Y (t) : t R}, be a real-valued stochastic process de ned on a probability space ( , A, P) The process is said to be strictly stationary if for any choice of the positive integer k and t1 , .., tk , t R, the joint distribution (in Rk ) of Y (t1 + t), ..., Y (tk + t) does not depend on t Clearly, if the process is Gaussian, it is strictly stationary if and only if for any choice of R, the expectation and covariance E(Y (t)) and Cov(Y (t), Y (t + )) do not depend on t We assume some mild regularity of the paths of the process Y such as that almost surely, they are Riemann integrable on every bounded interval For example, if the paths are as c` d-l` g, this follows easily.