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Part of the OXFORD STATISTICAL SCIENCE series describing the use of smoothing techniques in statistics with an emphasis on applications rather than detailed theory, and making extensive reference to S-Plus as a computing environment in which examples can be explored. S-Plus functions and example scripts are provided to implement the techniques.

Smoothing (Statistics) --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics --- Kernel functions.

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In this concise, evidence-based guide for educational leaders, the authors argue that two-year colleges can increase their rates of student success by discarding the traditional "cafeteria-style" model of course offerings and instead provide students with a "guided pathways" model in which more educationally coherent programs simplify students' choices without limiting their options and enable students to advance to further education and the labor market more quickly and at less cost.

Community colleges --- achieving the dream. --- advising. --- completion agenda. --- curriculum. --- developmental education. --- disadvantaged students. --- enrollment. --- graduation rates. --- guided pathways model. --- how improve success community college. --- online learning. --- postsecondary outcomes. --- program maps. --- transferring colleges. --- underserved.

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The data report presents the structural development of educational science and is commissioned every four years by Deutsche Gesellschaft für Erziehungswissenschaft (DGfE). The publication aims to inform the field-specialized public, education and higher education politics as well as the public about current developments in educational science as one of the largest fields at German universities. Particular attention is paid to study programs, students, degrees, human resources, research achievements and the promotion of young talents. The data report provides basic information on how educational science develops under the influence of recent changes and identifies the need for action in terms of the political field as well as higher education and education policy. Relevant information in the data report - for example on students, degrees and academic careers - is differentiated by gender. The DGfE thus fulfills its own claim to support gender equality. The data report is of particular importance for current discussions about securing training capacities for professional pedagogical professions and about academic careers. Der Datenreport ist eine regelmäßig alle vier Jahre von der Deutschen Gesellschaft für Erziehungswissenschaft (DGfE) in Auftrag gegebene Darstellung struktureller Entwicklungen der Erziehungswissenschaft. Er informiert die Fachöffentlichkeit, die Bildungs- und Hochschulpolitik sowie die Öffentlichkeit über Trends und den jeweils erreichten Entwicklungsstand der Erziehungswissenschaft als eines der größten Fächer an deutschen Hochschulen. Besonderes Augenmerk liegt auf den Indikatoren zu Studiengängen, Studienabschlüssen, Personal, Forschungsleistungen und Nachwuchsförderung.

Absolventen --- Bildungspolitik --- degree courses --- Dissertation --- doctorate --- educational policy --- educational science --- graduates --- graduation --- Habilitation --- job market --- Lehrerbildung --- Lehrerinnenbildung --- Nachwuchsförderung --- Personal --- personnel --- PhD --- promotion of young talents --- Promotion --- publication culture --- Publikationskultur --- science research --- Stellenmarkt --- Studienabschlüsse --- Studiengänge --- teacher education --- teacher training --- transitions --- Wissenschaftsforschung --- Übergänge --- education and higher education politics

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Beginning in the early 2000s, there was an upsurge of national concern over the state of the science and engineering job market that sparked a plethora of studies, commission reports, and a presidential initiative, all stressing the importance of maintaining American competitiveness in these fields. Science and Engineering Careers in the United States is the first major academic study to probe the issues that underlie these concerns. This volume provides new information on the economics of the postgraduate science and engineering job market, addressing su

Scientists --- Engineers --- Science --- Engineering --- Study and teaching (Higher) --- stem, science, engineering, job market, technology, career, professional, college, competition, american workers, industry, business, nonfiction, economy, growth, innovation, female doctorates, women, gender, diversity, foreign-born, immigration, graduates, recruitment, academe, patents, research papers, publication, knowledge, graduation, phds, postgraduate, employment, inefficiency, higher education, scientific dissemination, commerce, promotions.

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Nonparametric function estimation with stochastic data, otherwise known as smoothing, has been studied by several generations of statisticians. Assisted by the ample computing power in today's servers, desktops, and laptops, smoothing methods have been finding their ways into everyday data analysis by practitioners. While scores of methods have proved successful for univariate smoothing, ones practical in multivariate settings number far less. Smoothing spline ANOVA models are a versatile family of smoothing methods derived through roughness penalties, that are suitable for both univariate and multivariate problems. In this book, the author presents a treatise on penalty smoothing under a unified framework. Methods are developed for (i) regression with Gaussian and non-Gaussian responses as well as with censored lifetime data; (ii) density and conditional density estimation under a variety of sampling schemes; and (iii) hazard rate estimation with censored life time data and covariates. The unifying themes are the general penalized likelihood method and the construction of multivariate models with built-in ANOVA decompositions. Extensive discussions are devoted to model construction, smoothing parameter selection, computation, and asymptotic convergence.

Analysis of variance. --- Smoothing (Statistics). --- Spline theory. --- Analysis of variance --- Spline theory --- Smoothing (Statistics) --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- Spline functions --- ANOVA (Analysis of variance) --- Variance analysis --- Statistics. --- Statistical Theory and Methods. --- Curve fitting --- Graduation (Statistics) --- Roundoff errors --- Statistics --- Approximation theory --- Interpolation --- Mathematical statistics --- Experimental design --- Mathematical statistics. --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Statistical methods --- Statistics . --- Statistical analysis --- Statistical data --- Statistical science --- Econometrics