Statistical significance

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  • Medicine without statistics is quackery; statistics without medicine is numerology. Perhaps this is the main reason why clinicians should care about statistics. Statistics in medicine began in the early nineteenth century (it was called “the numerical method” then) and its debut involved disproving the most common and widely accepted medical treatment for millennia: bleeding. From ancient Rome until 1900, all physicians – from Galen to Avicenna to Benjamin Rush – strongly and clearly advocated bleeding as the treatment for most medical illnesses.

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  • Chapter 9 - Descriptive statistics, significance levels, and hypothesis testing. After reading this chapter, you should be able to: Explain the concept of the normal curve, assess data for its distribution and compare it to the normal curve, create a frequency distribution and polygon for each variable in a dataset, compute and interpret the mean, median, and mode for each variable in a dataset,...

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  • A: Basically, statistics is the “science of data.” There are three main tasks in statistics: (A) collection and organization, (B) analysis, and (C) interpretation of data. (A) Collection and organization of data: We will see several methods of organizing data: graphically (through the use of charts and graphs) and numerically (through the use of tables of data). The type of organization we do depends on the type of analysis we wish to perform.

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  • The idea for this book originated during a conversation in December 2006 with C. Deborah Laughton, Publisher, Methodology and Statistics, at The Guilford Press, about the challenges of teaching research seminars or other courses in which students conduct a thesis project. These students could be senior undergraduates in advanced programs, such as honors or specialization, or first-year graduate students.

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  • We do not find economically or statistically significant differences in fees (expenses, loads, or a measure of the total ownership cost of mutual fund shares) between SRI and similar conventional funds. Therefore, either there are no significant differences in the way fees are set for SRI and conventional funds, or the effects of those differences cancel out on average. Consistent with the results for before-fee performance and fees, we find that SRI funds obtain a higher after-fee risk-adjusted performance in terms of four-factor alpha than similar conventional funds. ...

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  • Applied statistics and probabilty for engineers_This is an introductory textbook for a first course in applied statistics and probability for undergraduate students in engineering and the physical or chemical sciences. These individuals play a significant role in designing and developing new products and manufacturing systems and processes, and they also improve existing systems. Statistical methods are an important tool in these activities because they provide the engineer with both descriptive and analytical methods for dealing with the variability in observed data.

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  • In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free grammar. We then extend the model to include a probabilistic treatment of both subcategorisation and wh-movement. Results on Wall Street Journal text show that the parser performs at 88.1/87.5% constituent precision/recall, an average improvement of 2.3% over (Collins 96). is derived from the analysis given in Generalized Phrase Structure Grammar (Gazdar et al. 95).

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  • This computerized study of the homonyms of elementary words (roughly equivalent to monosyllabic words) has allowed the compilation of exhaustive lists of homonym sets, using phonetic transcriptions from five different dictionaries. Of the 5,757 elementary words, 2,966 were involved in at least one homonym set, indicating that homonyms will present a significant problem in.

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  • This paper proposes to use monolingual collocations to improve Statistical Machine Translation (SMT). We make use of the collocation probabilities, which are estimated from monolingual corpora, in two aspects, namely improving word alignment for various kinds of SMT systems and improving phrase table for phrase-based SMT. The experimental results show that our method improves the performance of both word alignment and translation quality significantly.

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  • This paper presents a Bayesian decision framework that performs automatic story segmentation based on statistical modeling of one or more lexical chain features. Automatic story segmentation aims to locate the instances in time where a story ends and another begins. A lexical chain is formed by linking coherent lexical items chronologically. A story boundary is often associated with a significant number of lexical chains ending before it, starting after it, as well as a low count of chains continuing through it.

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  • This paper compares a number of generative probability models for a widecoverage Combinatory Categorial Grammar (CCG) parser. These models are trained and tested on a corpus obtained by translating the Penn Treebank trees into CCG normal-form derivations. According to an evaluation of unlabeled word-word dependencies, our best model achieves a performance of 89.9%, comparable to the figures given by Collins (1999) for a linguistically less expressive grammar. In contrast to Gildea (2001), we find a significant improvement from modeling wordword dependencies. ...

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  • We introduce a polynomial-time algorithm for statistical machine translation. This algorithm can be used in place of the expensive, slow best-first search strategies in current statistical translation architectures. The approach employs the stochastic bracketing transduction grammar (SBTG) model we recently introduced to replace earlier word alignment channel models, while retaining a bigram language model. The new algorithm in our experience yields major speed improvement with no significant loss of accuracy. ...

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  • (BQ) Part 1 book "A handbook of applied statistics in pharmacology" presents the following contents: Probability, distribution; mean, mode, median; variance, standard deviation, standard error, coefficient of variation; analysis of normality and homogeneity of variance; transformation of data and outliers; tests for significant differences,...

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  • Chapter 17 - Hypothesis testing. After studying this chapter you will be able to understand: The nature and logic of hypothesis testing, a statistically significant difference, the six-step hypothesis testing procedure, the differences between parametric and nonparametric tests and when to use each,...

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  • This is an unusual statistics book in several respects. It attempts to explain the statistical methodology needed to answer several biological questions. This is in contrast to books that try to teach statistical techniques and hope that the reader can find the appropriate contexts in which to use them. Many an applied scientist has seen this hope turn into despair, not really due to a fault of his own.

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  • Chapter 14 - Inferential data analysis. This chapter includes contents: Inferential statistics, uses for inferential statistics, sampling error, hypothesis testing, hypothesis testing procedures, statistical significance, parametric statistics, t-tests, types of t-test,...

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  • Chapter 17 - Hypothesis testing. After studying this chapter you will be able to understand: The nature and logic of hypothesis testing, a statistically significant difference, the six-step hypothesis testing procedure, the differences between parametric and nonparametric tests and when to use each, the factors that influence the selection of an appropriate test of statistical significance, how to interpret the various test statistics.

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  • In general, the health status at old age has an important individual and social relevance. The vulnerability is increasing by physiological and morphological changes in the organism and central nervous system during the ageing process. The indicators of physiological health are based on prevalence of disabilities and causes of death. In Germany the main causes of death are circulatory diseases, neoplasms, diseases of respiratory system and diseases of digestive system (Statistisches Bundesamt 2007a; Nolte, Shkolinikov & McKee 2000).

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  • Most people are aware of and concerned with the health effects of pesticide residues in the water they drink and the food they eat, but many are surprised to learn that pesticides are commonly found in air and rain. Scientific studies of pesticides in various atmospheric matrices (air, rain, snow, aerosols, and fog) have been ongoing for 40 years. When taken together, these studies, many of which are small and focused, provide a significant contribution to answering the questions when, where, how, and why pesticides are in the atmosphere.

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  • This difference is substantial and highly statistically significant in all specifications. These results are consistent with two different hypotheses. First, unobservable factors at the management company level could be associated with both the decision to specialize in SRI funds and higher fees and performance. In this case, socially responsible investing itself would not have any effect on performance or fees.

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