Data interpretation

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  • .Undergraduate Topics in Computer Science .Undergraduate Topics in Computer Science (UTiCS) delivers high-quality instructional content for undergraduates studying in all areas of computing and information science. From core foundational and theoretical material to final-year topics and applications, UTiCS books take a fresh, concise, and modern approach and are ideal for self-study or for a one- or two-semester course. The texts are all authored by established experts in their fields, reviewed by an international advisory board, and contain numerous examples and problems.

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  • Data can be defined as the quantitative or qualitative values of a variable. Data is plural of Datum which literally means to give or something given. Data is thought to be the lowest unit of information from which other measurements and analysis can be done. Data can be numbers, images, words, figures, facts or ideas. Data in itself cannot be understood and to get information from the data one must interpret it into meaningful information. There are various methods of interpreting data. Data sources are broadly classified into primary and secondary data....

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  • In data-oriented language processing, an annotated language corpus is used as a stochastic grammar. The most probable analysis of a new sentence is constructed by combining fragments from the corpus in the most probable way. This approach has been successfully used for syntactic analysis, using corpora with syntactic annotations such as the Penn Tree-bank. If a corpus with semantically annotated sentences is used, the same approach can also generate the most probable semantic interpretation of an input sentence. The present paper explains this semantic interpretation method. ...

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  • Previous approaches to instruction interpretation have required either extensive domain adaptation or manually annotated corpora. This paper presents a novel approach to instruction interpretation that leverages a large amount of unannotated, easy-to-collect data from humans interacting with a virtual world. We compare several algorithms for automatically segmenting and discretizing this data into (utterance, reaction) pairs and training a classifier to predict reactions given the next utterance.

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  • The automatic interpretation of noun-noun compounds is an important subproblem within many natural language processing applications and is an area of increasing interest. The problem is difficult, with disagreement regarding the number and nature of the relations, low inter-annotator agreement, and limited annotated data. In this paper, we present a novel taxonomy of relations that integrates previous relations, the largest publicly-available annotated dataset, and a supervised classification method for automatic noun compound interpretation.

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  • This paper describes a method for learning the countability preferences of English nouns from raw text corpora. The method maps the corpus-attested lexico-syntactic properties of each noun onto a feature vector, and uses a suite of memory-based classifiers to predict membership in 4 countability classes. We were able to assign countability to English nouns with a precision of 94.6%. ence. Knowledge of countability preferences is important both for the analysis and generation of English. In analysis, it helps to constrain the interpretations of parses. ...

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  • We describe a domain-independent semantic interpretation architecture suitable for spoken dialogue systems, which uses a decision-list method to effect a transparent combination of rule-based and data-driven approaches. The architecture has been implemented and evaluated in the context of a mediumvocabulary command and control task.

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  • When you have completed this chapter, you will be able to: Organize raw data into frequency distribution; produce a histogram, a frequency polygon, and a cumulative frequency polygon from quantitative data; develop and interpret a stem-and-leaf display; present qualitative data using such graphical techniques such as a clustered bar chart, a stacked bar chart, and a pie chart; detect graphic deceptions and use a graph to present data with clarity, precision, and efficiency.

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  • When you have completed this chapter, you will be able to: Conduct the sign test for single and dependent samples using the binomial and standard normal distributions as the test statistics, conduct a test of hypothesis for dependent samples using the Wilcoxon signed-rank test, conduct and interpret the Wilcoxon rank-sum test for independent samples,...

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  • (BQ) Part 2 book "ESG holter - Guide to electrocardiographic interpretation" presents the following contents: Presenting ECG holter data, clinical applications, other ECG recording systems, ECG holter and implanted cardioverter defibrillators, ECG report example, conclusion

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  • Chapter 10 - Fundamental interpretations made from financial statement data. Learning objectives of this chapter include: Explain why financial statement ratios are important, explain the importance of and calculate the return on assets (ROA), calculate and interpret margin and turnover using the adapted dupont model, explain the significance of and calculate the return on equity (ROE),...

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  • Chapter 2 - Describing data: frequency tables, frequency distributions, and graphic presentation. The main goals of this chapter are to: Make a frequency table for a set of data, organize data into a bar chart, present a set of data using a pie chart, create a frequency distribution for a data set, understand a relative frequency distribution, present data from a frequency distribution in a construct and interpret a cumulative frequency distribution.

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  • When you have completed this chapter, you will be able to: Explain the concept of central tendency, identify and compute the arithmetic mean, compute and interpret the weighted mean, determine the median, identify the mode, explain and apply measures of dispersion, compute and explain the variance and the standard deviation.

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  • When you have completed this chapter, you will be able to: Construct and interpret a dot plot, identify and compute measures of position, construct and analyze a box plot, compute and describe the coefficient of skewness, create and interpret a scatter diagram, develop and explain a contingency table.

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  • A key feature of procedural programming is the ability to create and debug code quickly and easily. Procedure Builder provides all of the functionality necessary for you to successfully develop and debug PL/SQL programs. This lesson enables you to manipulate PL/SQL code using Procedure Builder. At the end of this lesson, you should be able to  Identify the advantages of developing and debugging PL/SQL programs in Procedure Builder.  Manage program units by using the Object Navigator.  Execute program units and SQL statements by using the PL/SQL Interpreter.

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  • Statistical methods for survival data analysis have continued to flourish in the last two decades. Applications of the methods have been widened from their historical use in cancer and reliability research to business, criminology, epidemiology, and social and behavioral sciences. The third edition of Statistical Methods for Survival Data Analysis is intended to provide a comprehensive introduction of the most commonly used methods for analyzing survival data. It begins with basic definitions and interpretations of survival functions....

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  • A soft ground condition exists whenever construction loads a cohesive foundation soil beyond its preconsolidation stress, as often occurs with saturated clays and silts having SPT blow counts that are near zero. The paper recommends testing programs, testing methods and data interpretation techniques for developing design parameters for settlement and stability analyses. It hopes to move the state-of-practice closer to the state-of-the-art and thus is intended for geotechnical practitioners and teachers rather than researchers.

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  • 150 Practice ECGs: Interpretation and Review Third Edition Part I: How to Interpret ECGs Part II: 150 Practice ECGs Chapter 1: Baseline Data Part III: Interpretation and Comments Chapter 2: Morphologic Changes in P, QRS, ST, and T For Marilyn 150 Practice ECGs: Interpretation and Review Third Edition George J. Taylor, MD Professor of Medicine The Medical University of South Carolina The Ralph H. Johnson VA Medical Center Charleston, South Carolina, USA © 2006 George J. Taylor Published Blackwell Blackwell Blackwell by Blackwell Publishing Ltd Publishing, Inc.

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  • The data banks of the National Bureau of Economic Research contain time-series data on 2000 macroeconomic variables. Even if observations were available since the birth of Christ, the degrees of freedom in a model explaining gross national product in terms of all these variables would not turn positive for another two decades. If annual observations were restricted to the 30-year period from 1950 to 1979, the degrees of freedom deficit would be 1970.

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  • The biological sciences have become more quantitative and information-driven since emerging computational and mathematical tools facilitate collection and analysis of vast amounts of biological data. Complexity analysis of biological systems provides biological knowledge for the organization, management, and mining of biological data by using advanced computational tools. The biological data are inherently complex, nonuniform, and collected at multiple temporal and spatial scales.

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