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An introduction to the mathematical theory and financial models developed and used on Wall Street Providing both a theoretical and practical approach to the underlying mathematical theory behind financial models, Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach presents important concepts and results in measure theory, probability theory, stochastic processes, and stochastic calculus. Measure theory is indispensable to the rigorous development of probability theory and is also necessary to properly address martingale measures, the change of numeraire theory, and LIBOR market models. In addition, probability theory is presented to facilitate the development of stochastic processes, including martingales and Brownian motions, while stochastic processes and stochastic calculus are discussed to model asset prices and develop derivative pricing models. The authors promote a problem-solving approach when applying mathematics in real-world situations, and readers are encouraged to address theorems and problems with mathematical rigor. In addition, Measure, Probability, and Mathematical Finance features: A comprehensive list of concepts and theorems from measure theory, probability theory, stochastic processes, and stochastic calculus Over 500 problems with hints and select solutions to reinforce basic concepts and important theorems Classic derivative pricing models in mathematical finance that have been developed and published since the seminal work of Black and Scholes Measure, Probability, and Mathematical Finance: A Problem-Oriented Approach is an ideal textbook for introductory quantitative courses in business, economics, and mathematical finance at the upper-undergraduate and graduate levels. The book is also a useful reference for readers who need to build their mathematical skills in order to better understand the mathematical theory of derivative pricing models.
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Social sciences --- Research --- Statistical methods --- Longitudinal studies --- -Social sciences --- -Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- -Statistical methods --- -Research --- Behavioral sciences --- Research&delete& --- Social sciences - Research - Statistical methods --- Social sciences - Longitudinal studies
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Quantitative methods in social research --- Methods in social research (general) --- Mathematical statistics --- Social sciences --- Sciences sociales --- Research --- Fieldwork --- Recherche --- Recherche sur le terrain --- Statistical methods --- #SBIB:303H510 --- #SBIB:303H520 --- Methoden sociale wetenschappen: statistische technieken, algemeen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Social sciences - Research - Statistical methods --- Social sciences - Research --- Social sciences - Fieldwork
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Quantitative methods in social research --- Organization --- Social sciences --- #SBIB:316.334.2A15 --- #SBIB:303H12 --- Organisation --- Management --- Research --- Methodology. --- Statistical methods. --- Arbeidssociologische onderzoeksmethoden en technieken --- Methoden en technieken: sociale wetenschappen --- Methodology --- Statistical methods --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Research&delete& --- Organization - Research - Methodology --- Organization - Research - Statistical methods --- Social sciences - Statistical methods --- Social sciences - Research - Statistical methods
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This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are based partially in sound scientific rationale and partially in unfounded lore. Some examples of these “methodological urban legends” are characterized by manuscript critiques such as: (a) “your self-report measures suffer from common method bias”; (b) “your item-to-subject ratios are too low”; (c) “you can’t generalize these findings to the real world”; or (d) “your effect sizes are too low.What do these critiques mean, and what is their historical basis? More Statistical and Methodological Myths and Urban Legends catalogs several of these quirky practices and outlines proper research techniques. Topics covered include sample size requirements, missing data bias in correlation matrices, negative wording in survey research, and much more
Organization --- Social sciences --- #SBIB:316.334.2A15 --- #SBIB:303H12 --- Organisation --- Management --- Research --- Methodology. --- Statistical methods. --- Arbeidssociologische onderzoeksmethoden en technieken --- Methoden en technieken: sociale wetenschappen --- Methodology --- Statistical methods --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Research&delete& --- Organization - Research - Methodology --- Organization - Research - Statistical methods --- Social sciences - Statistical methods --- Social sciences - Research - Statistical methods
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Social sciences --- Multivariate analysis --- Research --- Mathematical models --- Statistical methods --- Data processing --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Multivariate distributions --- Multivariate statistical analysis --- Statistical analysis, Multivariate --- Analysis of variance --- Mathematical statistics --- Matrices --- Research&delete& --- Social sciences - Research - Mathematical models --- Social sciences - Research - Statistical methods --- Social sciences - Research - Data processing
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Survey Methodology is becoming a more structured field of research, deserving of more and more academic attention. The SAGE Handbook of Survey Methodology explores both the increasingly scientific endeavour of surveys and their growing complexity, as different data collection modes and information sources are combined. The handbook takes a global approach, with a team of international experts looking at local and national specificities, as well as problems of cross-national, comparative survey research. The chapters are organized into seven major sections, each of which represents a stage in the survey life-cycle: Surveys and Societies Planning a Survey Measurement Sampling Data Collection Preparing Data for Use Assessing and Improving Data Quality The SAGE Handbook of Survey Methodology is a landmark and essential tool for any scholar within the social sciences.
Surveys --- Social surveys --- Social sciences --- #SBIB:303H30 --- #SBIB:303H32 --- Government surveys --- Mathematical geography --- Methodology. --- Statistical methods. --- Kwalitatieve methoden: algemeen --- Waarneming en participerende waarneming, gecontroleerde observatie, groepsdiscussie (vragenlijsten, interviews, experimenten) --- Methodology --- Research --- Statistical methods --- Umfrage. --- Empirische Sozialforschung. --- Methodologie. --- Methodenlehre --- Methodik --- Wissenschaftstheorie --- Logik --- Methode --- Empirische Soziologie --- Sozialforschung --- Soziologie --- Bevölkerungsumfrage --- Repräsentativumfrage --- Meinungsbefragung --- Meinungsumfrage --- Volksbefragung --- Befragung --- Umfragen --- Demoskopie --- Civilization --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Community surveys --- Surveys, Social --- Surveys - Methodology --- Social surveys - Methodology --- Social sciences - Research - Statistical methods
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A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method. Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.
Social sciences --- Analysis of variance --- Research --- Statistical methods --- ANOVA (Analysis of variance) --- Variance analysis --- Mathematical statistics --- Experimental design --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Research&delete& --- #SBIB:303H10 --- #SBIB:303H520 --- Methoden en technieken: algemene handboeken en reeksen --- Methoden sociale wetenschappen: techniek van de analyse, algemeen --- Quantitative methods in social research --- Analysis of variance. --- Statistical methods. --- Social sciences - Research - Statistical methods
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Mathematical statistics --- Longitudinal method --- Medicine --- Medical sciences --- Social sciences --- Research --- Statistical methods --- 519.237 --- 303.7 --- Multivariate statistical methods --- Analysetechnieken. Statistische analyse --(sociaal onderzoek) --- 303.7 Analysetechnieken. Statistische analyse --(sociaal onderzoek) --- 519.237 Multivariate statistical methods --- Behavioral sciences --- Human sciences --- Sciences, Social --- Social science --- Social studies --- Civilization --- Clinical sciences --- Medical profession --- Human biology --- Life sciences --- Pathology --- Physicians --- Basic medical sciences --- Basic sciences, Medical --- Biomedical sciences --- Health sciences --- Preclinical sciences --- Sciences, Medical --- Longitudinal research --- Longitudinal studies --- Methodology --- Research&delete& --- Health Workforce --- Medicine - Research - Statistical methods --- Medical sciences - Research - Statistical methods --- Social sciences - Research - Statistical methods
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