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| department of math and statistics: Mathematical Statistics Jun Shao, 2008-02-03 This graduate textbook covers topics in statistical theory essential for graduate students preparing for work on a Ph.D. degree in statistics. This new edition has been revised and updated and in this fourth printing, errors have been ironed out. The first chapter provides a quick overview of concepts and results in measure-theoretic probability theory that are useful in statistics. The second chapter introduces some fundamental concepts in statistical decision theory and inference. Subsequent chapters contain detailed studies on some important topics: unbiased estimation, parametric estimation, nonparametric estimation, hypothesis testing, and confidence sets. A large number of exercises in each chapter provide not only practice problems for students, but also many additional results. |
| department of math and statistics: Ranked Set Sampling Zehua Chen, Zhidong Bai, Bimal Sinha, 2013-03-09 The first book on the concept and applications of ranked set sampling. It provides a comprehensive review of the literature, and it includes many new results and novel applications. The detailed description of various methods illustrated by real or simulated data makes it useful for scientists and practitioners in application areas such as agriculture, forestry, sociology, ecological and environmental science, and medical studies. It can serve as a reference book and as a textbook for a short course at the graduate level. |
| department of math and statistics: Statistics in Action Jerald F. Lawless, 2014-03-03 Commissioned by the Statistical Society of Canada (SSC), Statistics in Action: A Canadian Outlook helps both general readers and users of statistics better appreciate the scope and importance of statistics. It presents the ways in which statistics is used while highlighting key contributions that Canadian statisticians are making to science, techno |
| department of math and statistics: Mathematical Statistics Thomas S. Ferguson, 2014-07-10 Mathematical Statistics: A Decision Theoretic Approach presents an investigation of the extent to which problems of mathematical statistics may be treated by decision theory approach. This book deals with statistical theory that could be justified from a decision-theoretic viewpoint. Organized into seven chapters, this book begins with an overview of the elements of decision theory that are similar to those of the theory of games. This text then examines the main theorems of decision theory that involve two more notions, namely the admissibility of a decision rule and the completeness of a class of decision rules. Other chapters consider the development of theorems in decision theory that are valid in general situations. This book discusses as well the invariance principle that involves groups of transformations over the three spaces around which decision theory is built. The final chapter deals with sequential decision problems. This book is a valuable resource for first-year graduate students in mathematics. |
| department of math and statistics: Pulling Rabbits Out of Hats David Wollkind, Bonni J. Dichone, 2021 Pulling Rabbits Out of Hats: Using Mathematical Modeling in the Material, Biophysical, Fluid Mechanical, and Chemical Sciences focuses on those assumptions made during applied mathematical modeling in which the phenomenological data and the model predictions are self-consistent. This comprehensive reference demonstrates how to employ a variety of mathematical techniques to quantify a number of problems from the material, biophysical, fluid mechanical, and chemical sciences. In doing so, methodology of modelling, analysis, and result generation are all covered-- |
| department of math and statistics: Statistics for Mathematicians Victor M. Panaretos, 2016-06-01 This textbook provides a coherent introduction to the main concepts and methods of one-parameter statistical inference. Intended for students of Mathematics taking their first course in Statistics, the focus is on Statistics for Mathematicians rather than on Mathematical Statistics. The goal is not to focus on the mathematical/theoretical aspects of the subject, but rather to provide an introduction to the subject tailored to the mindset and tastes of Mathematics students, who are sometimes turned off by the informal nature of Statistics courses. This book can be used as the basis for an elementary semester-long first course on Statistics with a firm sense of direction that does not sacrifice rigor. The deeper goal of the text is to attract the attention of promising Mathematics students. |
| department of math and statistics: Mathematical Statistics and Applications Marc Moore, Constance van Eeden, 2003 |
| department of math and statistics: All of Statistics Larry Wasserman, 2013-12-11 Taken literally, the title All of Statistics is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data. |
| department of math and statistics: Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education Carmen Batanero, Gail Burrill, Chris Reading, 2011-07-31 Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education results from the Joint ICMI/IASE Study Teaching Statistics in School Mathematics: Challenges for Teaching and Teacher Education. Oriented to analyse the teaching of statistics in school and to recommend improvements in the training of mathematics teachers to encourage success in preparing statistically literate students, the volume provides a picture of the current situation in both the teaching of school statistics and the pre-service education of mathematics teachers. A primary goal of Teaching Statistics in School Mathematics-Challenges for Teaching and Teacher Education is to describe the essential elements of statistics, teacher’s professional knowledge and their learning experiences. Moreover, a research agenda that invites new research, while building from current knowledge, is developed. Recommendations about strategies and materials, available to train prospective teachers in university and in-service teachers who have not been adequately prepared, are also accessible to the reader. |
| department of math and statistics: Mathematics Education Jacqueline Dewar, Pao-sheng Hsu, Harriet Pollatsek, 2016-11-26 Many in the mathematics community in the U.S. are involved in mathematics education in various capacities. This book highlights the breadth of the work in K-16 mathematics education done by members of US departments of mathematical sciences. It contains contributions by mathematicians and mathematics educators who do work in areas such as teacher education, quantitative literacy, informal education, writing and communication, social justice, outreach and mentoring, tactile learning, art and mathematics, ethnomathematics, scholarship of teaching and learning, and mathematics education research. Contributors describe their work, its impact, and how it is perceived and valued. In addition, there is a chapter, co-authored by two mathematicians who have become administrators, on the challenges of supporting, evaluating, and rewarding work in mathematics education in departments of mathematical sciences. This book is intended to inform the readership of the breadth of the work and to encourage discussion of its value in the mathematical community. The writing is expository, not technical, and should be accessible and informative to a diverse audience. The primary readership includes all those in departments of mathematical sciences in two or four year colleges and universities, and their administrators, as well as graduate students. Researchers in education may also find topics of interest. Other potential readers include those doing work in mathematics education in schools of education, and teachers of secondary or middle school mathematics as well as those involved in their professional development. |
| department of math and statistics: Matrix Positivity Charles R. Johnson, Ronald L. Smith, Michael J. Tsatsomeros, 2020-10 This comprehensive reference, for mathematical, engineering and social scientists, covers matrix positivity classes and their applications. |
| department of math and statistics: Theoretical Statistics D.R. Cox, D.V. Hinkley, 1979-09-06 A text that stresses the general concepts of the theory of statistics Theoretical Statistics provides a systematic statement of the theory of statistics, emphasizing general concepts rather than mathematical rigor. Chapters 1 through 3 provide an overview of statistics and discuss some of the basic philosophical ideas and problems behind statistical procedures. Chapters 4 and 5 cover hypothesis testing with simple and null hypotheses, respectively. Subsequent chapters discuss non-parametrics, interval estimation, point estimation, asymptotics, Bayesian procedure, and deviation theory. Student familiarity with standard statistical techniques is assumed. |
| department of math and statistics: Maths Enrichment Ric Publications Staff, 1997 The book contains blackline masters of stimulating activities in mathematics.._ |
| department of math and statistics: Scientific Manpower and Education United States. Congress. House. Committee on Science and Astronautics, 1959 |
| department of math and statistics: Count Me In Della Dumbaugh, Deanna Haunsperger, 2022-02-24 This groundbreaking work explores the powerful role of communities in mathematics. It introduces readers to twenty-six different mathematical communities and addresses important questions about how they form, how they thrive, and how they advance individuals and the group as a whole. The chapters celebrate how diversity and sameness bind colleagues together, showing how geography, gender, or graph theory can create spaces for colleagues to establish connections in the discipline. They celebrate outcomes measured by mathematical results and by increased interest in studying mathematics. They highlight the value of relationships with peers and colleagues at various stages of their careers. Together, these stories offer a guide—rather than a template—for building and sustaining a mathematical community. They call attention to critical strategies of rotating leadership and regular assessment and evaluation of goals and programs, and promote an ongoing awareness of the responsibilities of life that impinge on mathematical creativity and contributions. Whether you are giving thought to starting a group, joining one already in existence, or encouraging a colleague to participate in the broader mathematical community, this book will meet you where you are—and move you beyond. It contains a plethora of ideas to foster a sense of belonging in the exciting discipline of mathematics. |
| department of math and statistics: Asymptotics in Statistics Lucien Le Cam, Grace Lo Yang, 2012-12-06 This is the second edition of a coherent introduction to the subject of asymptotic statistics as it has developed over the past 50 years. It differs from the first edition in that it is now more 'reader friendly' and also includes a new chapter on Gaussian and Poisson experiments, reflecting their growing role in the field. Most of the subsequent chapters have been entirely rewritten and the nonparametrics of Chapter 7 have been amplified. The volume is not intended to replace monographs on specialized subjects, but will help to place them in a coherent perspective. It thus represents a link between traditional material - such as maximum likelihood, and Wald's Theory of Statistical Decision Functions -- together with comparison and distances for experiments. Much of the material has been taught in a second year graduate course at Berkeley for 30 years. |
| department of math and statistics: The Art of Problem Posing Stephen I. Brown, Marion I. Walter, 2005-01-15 This book encourages readers to shift their thinking about problem posing from the other to themselves (i.e. that they can develop problems themselves) and offers a broader conception of what can be done with problems. |
| department of math and statistics: Annual Report for Fiscal Year ... National Science Foundation (U.S.), 1958 |
| department of math and statistics: War Stories from Applied Math Robert Fraga, 2007 These projects are adaptations of transcripts made at a workship at Marquette University in Milwaukee, WI in 1996. This workshop ... brought together four mathematicians ... representatives from industry, and an audience of mathematicans interested in trying out the ideas presented to them. |
| department of math and statistics: Number Theory and Applications S.D. Adhikari, B. Ramakrishnan, 2009-06-15 This collection of articles contains the proceedings of the two international conferences (on Number Theory and Cryptography) held at the Harish - Chandra Research Institute. In recent years the interest in number theory has increased due to its applications in areas like error-correcting codes and cryptography. These proceedings contain papers in various areas of number theory, such as combinatorial, algebraic, analytic and transcendental aspects, arithmetic algebraic geometry, as well as graph theory and cryptography. While some papers do contain new results, several of the papers are expository articles that mention open questions, which will be useful to young researchers. |
| department of math and statistics: Lectures on Algebraic Statistics Mathias Drton, Bernd Sturmfels, Seth Sullivant, 2009-04-25 How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of algebraic statistics. In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models. |
| department of math and statistics: Stratifying Endomorphism Algebras Edward Cline, Brian Parshall, Leonard L. Scott, 1996 This paper presents a systematic study of the relationships between the representation theories of [italic capital]R and [italic capital]A, especially those involving actual or potential quasi-hereditary structures on the latter algebra. Our original motivation comes from the theory of Schur algebras, work of Soergel on the Bernstein-Gelfand-Gelfand category [script capital]O, and resent results of Dlab-Heath-Marko realizing certain endomorphism algebras as quasi-hereditary algebras. We synthesize common features of all these examples, and go beyond them in a number of new directions. |
| department of math and statistics: Groups, Rings, Lie and Hopf Algebras , 2003-03-31 The volume is almost entirely composed of the research and expository papers by the participants of the International Workshop Groups, Rings, Lie and Hopf Algebras, which was held at the Memorial University of Newfoundland, St. John's, NF, Canada. All four areas from the title of the workshop are covered. In addition, some chapters touch upon the topics, which belong to two or more areas at the same time. Audience: The readership targeted includes researchers, graduate and senior undergraduate students in mathematics and its applications. |
| department of math and statistics: Hearings United States. Congress. House. Committee on Science and Astronautics, 1959 |
| department of math and statistics: Mathematical and Statistical Methods in Food Science and Technology Daniel Granato, Gastón Ares, 2014-03-03 Mathematical and Statistical Approaches in Food Science and Technology offers an accessible guide to applying statistical and mathematical technologies in the food science field whilst also addressing the theoretical foundations. Using clear examples and case-studies by way of practical illustration, the book is more than just a theoretical guide for non-statisticians, and may therefore be used by scientists, students and food industry professionals at different levels and with varying degrees of statistical skill. |
| department of math and statistics: Peterson's Graduate Programs in Business, Education, Health, Information Studies, Law & Social Work 2012 Peterson's, 2012-05-15 Peterson's Graduate Programs in Business, Education, Health, Information Studies, Law & Social Work 2012 contains a wealth of info on accredited institutions offering graduate degrees in these fields. Up-to-date info, collected through Peterson's Annual Survey of Graduate and Professional Institutions, provides valuable data on degree offerings, professional accreditation, jointly offered degrees, part-time & evening/weekend programs, postbaccalaureate distance degrees, faculty, students, requirements, expenses, financial support, faculty research, and unit head and application contact information. There are helpful links to in-depth descriptions about a specific graduate program or department, faculty members and their research, and more. Also find valuable articles on financial assistance, the graduate admissions process, advice for international and minority students, and facts about accreditation, with a current list of accrediting agencies. |
| department of math and statistics: Undergraduate Mathematics for the Life Sciences Glenn Ledder, Jenna P. Carpenter, Timothy D. Comar, 2013 There is a gap between the extensive mathematics background that is beneficial to biologists and the minimal mathematics background biology students acquire in their courses. The result is an undergraduate education in biology with very little quantitative content. New mathematics courses must be devised with the needs of biology students in mind. In this volume, authors from a variety of institutions address some of the problems involved in reforming mathematics curricula for biology students. The problems are sorted into three themes: Models, Processes, and Directions. It is difficult for mathematicians to generate curriculum ideas for the training of biologists so a number of the curriculum models that have been introduced at various institutions comprise the Models section. Processes deals with taking that great course and making sure it is institutionalized in both the biology department (as a requirement) and in the mathematics department (as a course that will live on even if the creator of the course is no longer on the faculty). Directions looks to the future, with each paper laying out a case for pedagogical developments that the authors would like to see. |
| department of math and statistics: Maximality Properties in Numerical Semigroups and Applications to One-Dimensional Analytically Irreducible Local Domains Valentina Barucci, David E. Dobbs, Marco Fontana, 1997 In Chapter I, various (numerical) semigroup-theoretic concepts and constructions are introduced and characterized. Applications in Chapter II are made to the study of Noetherian local one-dimensional analytically irreducible integral domains, especially for the Gorenstein, maximal embedding dimension, and Arf cases, as well as to the so-called Kunz case, a pervasive kind of domain of Cohen-Macaulay type 2. |
| department of math and statistics: The Elements of Statistical Learning Trevor Hastie, Robert Tibshirani, Jerome Friedman, 2013-11-11 During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting. |
| department of math and statistics: Statistics without Mathematics David J. Bartholomew, 2015-10-19 This is a book about the ideas that drive statistics. It is an ideal primer for students who need an introduction to the concepts of statistics without the added confusion of technical jargon and mathematical language. It introduces the intuitive thinking behind standard procedures, explores the process of informal reasoning, and uses conceptual frameworks to provide a foundation for students new to statistics. It showcases the expertise we have all developed from living in a data saturated society, increases our statistical literacy and gives us the tools needed to approach statistical mathematics with confidence. Key topics include: Variability Standard Distributions Correlation Relationship Sampling Inference An engaging, informal introduction this book sets out the conceptual tools required by anyone undertaking statistical procedures for the first time or for anyone needing a fresh perspective whilst studying the work of others. |
| department of math and statistics: Modern Stochastics and Applications Volodymyr Korolyuk, Nikolaos Limnios, Yuliya Mishura, Lyudmyla Sakhno, Georgiy Shevchenko, 2014-01-30 This volume presents an extensive overview of all major modern trends in applications of probability and stochastic analysis. It will be a great source of inspiration for designing new algorithms, modeling procedures and experiments. Accessible to researchers, practitioners, as well as graduate and postgraduate students, this volume presents a variety of new tools, ideas and methodologies in the fields of optimization, physics, finance, probability, hydrodynamics, reliability, decision making, mathematical finance, mathematical physics and economics. Contributions to this Work include those of selected speakers from the international conference entitled “Modern Stochastics: Theory and Applications III,” held on September 10 –14, 2012 at Taras Shevchenko National University of Kyiv, Ukraine. The conference covered the following areas of research in probability theory and its applications: stochastic analysis, stochastic processes and fields, random matrices, optimization methods in probability, stochastic models of evolution systems, financial mathematics, risk processes and actuarial mathematics and information security. |
| department of math and statistics: Notices of the American Mathematical Society American Mathematical Society, 1992 |
| department of math and statistics: Resources for Preparing Middle School Mathematics Teachers Cheryl Beaver, Laurie J. Burton, Maria Gueorguieva Gargova Fung, Klay Kruczek, 2013 Cheryl Beaver, Laurie Burton, Maria Fung, Klay Kruczek, editors--Cover. |
| department of math and statistics: Phantom Homology Melvin Hochster, Craig Huneke, 1993 This book uses a powerful new technique, tight closure, to provide insight into many different problems that were previously not recognized as related. The authors develop the notion of weakly Cohen-Macaulay rings or modules and prove some very general acyclicity theorems. These theorems are applied to the new theory of phantom homology, which uses tight closure techniques to show that certain elements in the homology of complexes must vanish when mapped to well-behaved rings. These ideas are used to strengthen various local homological conjectures. Initially, the authors develop the theory in positive characteristic, but it can be extended to characteristic 0 by the method of reduction to characteristic $p$. The book would be suitable for use in an advanced graduate course in commutative algebra. |
| department of math and statistics: Density of Prime Divisors of Linear Recurrences Christian Ballot, 1995 A general density theory of the set of prime divisors of a certain family of linear recurring sequences with constant coefficients, a family which is defined for any order recursion, is built up from the work of Lucas, Laxton, Hasse, and Lagarias. In particular, in this theory the notion of the rank of a prime divisor as well as the notion of a Companion Lucas sequence (Lucas), the group associated with a given second-order recursion (Laxton), and the effective computation of densities (Hasse and Lagarias) are first combined and then generalized to any order recursion. |
| department of math and statistics: Statistical Evaluation of Diagnostic Performance Kelly H. Zou, Aiyi Liu, Andriy I. Bandos, Lucila Ohno-Machado, Howard E. Rockette, 2016-04-19 Statistical evaluation of diagnostic performance in general and Receiver Operating Characteristic (ROC) analysis in particular are important for assessing the performance of medical tests and statistical classifiers, as well as for evaluating predictive models or algorithms. This book presents innovative approaches in ROC analysis, which are releva |
| department of math and statistics: Newsletter , 1993 |
| department of math and statistics: Statistical Methods for Reliability Data William Q. Meeker, Luis A. Escobar, Francis G. Pascual, 2022-01-24 An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic. |
| department of math and statistics: Recent Developments in Mathematical, Statistical and Computational Sciences D. Marc Kilgour, Herb Kunze, Roman Makarov, Roderick Melnik, Xu Wang, 2021-08-29 This book constitutes an up-to-date account of principles, methods, and tools for mathematical and statistical modelling in a wide range of research fields, including medicine, health sciences, biology, environmental science, engineering, physics, chemistry, computation, finance, economics, and social sciences. It presents original solutions to real-world problems, emphasizes the coordinated development of theories and applications, and promotes interdisciplinary collaboration among mathematicians, statisticians, and researchers in other disciplines. Based on a highly successful meeting, the International Conference on Applied Mathematics, Modeling and Computational Science, AMMCS 2019, held from August 18 to 23, 2019, on the main campus of Wilfrid Laurier University, Waterloo, Canada, the contributions are the results of submissions from the conference participants. They provide readers with a broader view of the methods, ideas and tools used in mathematical, statistical and computational sciences. |
| department of math and statistics: Inference, Asymptotics, and Applications Nancy Reid, Torben Martinussen, 2017-03-10 This book showcases the innovative research of Professor Skovgaard, by providing in one place a selection of his most important and influential papers. Introductions by colleagues set in context the highlights, key achievements, and impact, of each work. This book provides a survey of the field of asymptotic theory and inference as it was being pushed forward during an exceptionally fruitful time. It provides students and researchers with an overview of many aspects of the field. |
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Department of Planning and Development - Fairfax County
The mission of the Department of Planning and Development is to promote livable communities which enhance the quality of life for the present and the future. Our purpose is to provide …
Find Your Local Department - Virginia Department of Social …
Many questions or issues can only be resolved through your local department of social services agency. To find your local department of social services, please either use the search bar below …
Reston District Police Station | Police - Fairfax County
The motto for Reston Station is "Engaging our Community to Enhance a Solid Foundation of Trust". The Reston area continues to be one of the safest communities in Fairfax County, and it is our …
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To provide residents with convenient, accessible care, the Fairfax County Health Department is offering walk-in hours for immunizations, pregnancy testing, maternity intake services, …
Health Department - Fairfax County
Fairfax County Health Department provides services at locations throughout the county, Monday to Friday, 8 a.m. to 4:30 p.m. The Health Department’s main information line is 703-246-2411. The …
Office Locations | Family Services - Fairfax County
We support families and county residents of all ages and stages of life. Join our online community and engage with us through social media. #FairfaxCountyFamilyServices.
U.S. Department of State – Home
6 days ago · Leading America’s foreign policy to advance the interests and security of the American people. The American Revolution gave birth to a nation and helped define its people. …
List of federal agencies in Northern Virginia - Wikipedia
The following Federal Agencies are headquartered in Northern Virginia. Agencies with approximately 10,000+ employees, or a $10 billion+ budget are in bold.
Official News and Information from the Fairfax County Police Department
Fairfax County, VA – The Fairfax County Police Department actively engages with the community by participating in and hosting a variety of events. These include police district station events, …
DEPARTMENT Definition & Meaning | Dictionary.com
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