Integrating Food Production and Biodiversity
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Kwame Nkrumah University of Science and Technology, Kumasi
KWAME NKRUMAH UNIVERSITY OF SCIENCE AND TECHNOLOGY, KUMASI, GHANA Assessing the Social Impacts of Illegal Gold Mining Activities at Dunkwa-On-Offin by Judith Selassie Garr (B.A, Social Science) A Thesis submitted to the Department of Building Technology, College of Art and Built Environment in partial fulfilment of the requirement for a degree of MASTER OF SCIENCE NOVEMBER, 2018 DECLARATION I hereby declare that this work is the result of my own original research and this thesis has neither in whole nor in part been prescribed by another degree elsewhere. References to other people’s work have been duly cited. STUDENT: JUDITH S. GARR (PG1150417) Signature: ........................................................... Date: .................................................................. Certified by SUPERVISOR: PROF. EDWARD BADU Signature: ........................................................... Date: ................................................................... Certified by THE HEAD OF DEPARTMENT: PROF. B. K. BAIDEN Signature: ........................................................... Date: ................................................................... i ABSTRACT Mining activities are undertaken in many parts of the world where mineral deposits are found. In developing nations such as Ghana, the activity is done both legally and illegally, often with very little or no supervision, hence much damage is done to the water bodies where the activities are carried out. This study sought to assess the social impacts of illegal gold mining activities at Dunkwa-On-Offin, the capital town of Upper Denkyira East Municipality in the Central Region of Ghana. The main objectives of the research are to identify factors that trigger illegal mining; to identify social effects of illegal gold mining activities on inhabitants of Dunkwa-on-Offin; and to suggest effective ways in curbing illegal mining activities. Based on the approach to data collection, this study adopts both the quantitative and qualitative approach. -
In This Issue
SCASA: SOUTHERN CALIFORNIA CHA P- E-Tidings Newsletter TER OF THE AMERI- CAN STATISTICAL ASSOCIATION SCASA Events and News VOLUME 8, ISSUES 1 - 2 JANUARY - FEBRUARY 2019 In This Issue Page 2: New SCASA board Pages 3-4: Presidential address Page 5: Book Club Page 6: Online store Page 7: Statistics Poster competition Page 8: DataFest Page 9: Careers Day Page 10: Applied Statistics Workshop Page 11: Traveling course Page 12: Job Opening Announcement Page 13: Dr. Normalcurvesaurus, Ph.D. presents The answer is at the bottom of this issue. http://community.amstat.org/scasa/newsletters VOLUME 8, ISSUES 1 - 2 P A G E 2 SCASA Officers 2019-2020 : CONGRATULATIONS TO ALL ELECTED AND RE-ELECTED!!! We have the newly elected SCASA board!!! Congratulations to Everyone!!! President: James Joseph, AKAKIA [[email protected]] President-Elect: Rebecca Le, County of Riverside [[email protected]] Immediate Past President: Olga Korosteleva, CSULB [[email protected]] Treasurer: Olga Korosteleva, CSULB [[email protected]] Secretary: Michael Tsiang, UCLA [[email protected]] Vice President of Professional Affairs: Anna Liza Antonio, Enterprise Analytics [[email protected]] Vice President of Academic Affairs: Shujie Ma, UCR [[email protected]] Vice President for Student Affairs: Anna Yu Lee, APU and Claremont Graduate University [[email protected]] The ASA Council of Chapters Representative: Harold Dyck, CSUSB [[email protected]] ENewsletter Editor-in-Chief: Olga Korosteleva, CSULB [[email protected]] Chair of the Applied Statistics Workshop Committee: James Joseph, AKAKIA [[email protected]] Treasurer of the Applied Statistics Workshop: Rebecca Le, County of Riverside [[email protected]] Webmaster: Anthony Doan, CSULB [[email protected]] http://community.amstat.org/scasa/newsletters P A G E 3 VOLUME 8, ISSUES 1 - 2 “GROW STRONG” Presidential Address Southern California may be the most diverse job market in the United States, if not the world. -
Stats: Data and Models We’Ve Taken This Principle Still Further
Sample Preface. Not for Distribution. PREFACE tats: Data and Models, fifth edition, has been especially exciting to develop. The book you hold steps beyond our previous editions in several important ways. Of Scourse, we’ve kept our conversational style and anecdotes,1 but we’ve enriched that material with tools for teaching about randomness, sampling distribution models, and inference throughout the book. And we’ve expanded discussions of models for data to introduce models with more than two variables earlier in the text. We’ve taken our inspiration both from our experience in the classroom and from the 2016 revision of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) report adopted by the American Statistical Association. As a result, we increased the text’s innovative uses of technology to encourage more statistical thinking, while maintaining its traditional core concepts and coverage. You’ll notice that, to expand our attention beyond just one or two variables, we’ve adjusted the order of some topics. Innovations Technology One of the new GAISE guidelines states: Use technology to explore concepts and analyze data. We think a modern statistics text should recognize from the start that statistics is practiced with technology. And so should our students. You won’t find tedious calcula- tions worked by hand. You will find equation forms that favor intuition over calculation. You’ll find extensive use of real data—even large datasets. Throughout, you’ll find a focus on statistical thinking rather than calculation. The question that motivates each of our hundreds of examples is not “How do you calculate the answer?” but “How do you think about the answer?” For this edition of Stats: Data and Models we’ve taken this principle still further. -
Introductory Statistics
Statistics 100b/500b: Introductory Statistics Jay Emerson Assistant Professor of Statistics Yale University [email protected] TIME: Monday, Wednesday, and Friday 10:30-11:20 (with a special note regarding the Friday classes). CLASSROOM: Mason 211. Note the change from the original location, OML 203, which is not a lecture hall. We apologize for the confusion. TEACHIING FELLOWS (as of 1/9): Anna Kochetkova Qi Yan [email protected] [email protected] This course offers a foundation for statistical reasoning, emphasizing how statistics can help us to better understand the world. Topics include numerical and graphical summaries of data, data acquisition and experimental design, probability, hypothesis testing, confidence intervals, correlation and regression. Students will learn how to apply statistical concepts to data, analyzing and reaching conclusions to real-world problems. There are no prerequisites, and the course is intended for non-majors. I will assume only that students are familiar with elementary algebraic notation at the high school level. Regular problem sets (often daily, very short) will involve a heavy dose of common sense, traditional mathematical exercises, data analysis, and basic simulation techniques. Two short midterm exams (in addition to the final exam) will help students synthesize the material. Upon completion of this course, students should be able to think critically about data, to use graphical and numerical summaries, to apply standard statistical inference procedures, and to draw conclusions from such analyses. This is an introductory course with no prerequisites. It is not intended for students majoring in mathematics or the sciences, or for students who have strong mathematical or computational experience. -
The R Project for Statistical Computing a Free Software Environment For
The R Project for Statistical Computing A free software environment for statistical computing and graphics that runs on a wide variety of UNIX platforms, Windows and MacOS OpenStat OpenStat is a general-purpose statistics package that you can download and install for free. It was originally written as an aid in the teaching of statistics to students enrolled in a social science program. It has been expanded to provide procedures useful in a wide variety of disciplines. It has a similar interface to SPSS SOFA A basic, user-friendly, open-source statistics, analysis, and reporting package PSPP PSPP is a program for statistical analysis of sampled data. It is a free replacement for the proprietary program SPSS, and appears very similar to it with a few exceptions TANAGRA A free, open-source, easy to use data-mining package PAST PAST is a package created with the palaeontologist in mind but has been adopted by users in other disciplines. It’s easy to use and includes a large selection of common statistical, plotting and modelling functions AnSWR AnSWR is a software system for coordinating and conducting large-scale, team-based analysis projects that integrate qualitative and quantitative techniques MIX An Excel-based tool for meta-analysis Free Statistical Software This page links to free software packages that you can download and install on your computer from StatPages.org Free Statistical Software This page links to free software packages that you can download and install on your computer from freestatistics.info Free Software Information and links from the Resources for Methods in Evaluation and Social Research site You can sort the table below by clicking on the column names. -
Jcccjournaljune2020.Pdf
JOURNAL OF CONTENT, COMMUNITY&COMMUNICATION ISSN: 2395-7514 (Print), 2456-9011 (Online) Volume 11, Year 6, June –2020 Scopus, UGC CARE LIST and ICI Indexed Amity School of Communication, Amity University Madhya Pradesh, Gwalior The views expressed in the articles are those of the contributors and not necessarily of the Editorial Board or the Institute. The Editorial Board invites original, unpublished contributions in the form of research papers, articles, book reviews and case studies. No part of this publication may be reproduced or transmitted in any form or by any means or stored in any archival system of any nature without prior written permission. Application for permission for use of copyright material including permission to reproduce extracts in other published works shall be made to the publishers. Full acknowledgement of author, publisher and source must be given. i Call for Papers Dear Sir / Ma‟am It gives me immense pleasure to inform you that Amity School of Communication, Amity University Madhya Pradesh, Gwalior, has successfully published tenvolumes of its referred and peer-reviewed journal named “Journal of Content, Community & Communication”[ISSN: 2395-7514 (Print) & 2456-9011 (Online)] Scopus, UGC CARE LIST and ICI Index. This is a call for papers to all academicians/industry champions, like your good self to contribute for the upcoming issue which will be focused on “Media and COVID-19”. May I also, request you to circulate this among your colleagues, peers and friends for their contribution to JCCC. Manuscript must be typed in Microsoft Word Format, as per JCCCGuidelines given on www.amity.edu/gwalior/jccc. -
Dissertation Submitted in Partial Satisfaction of the Requirements for the Degree Doctor of Philosophy in Statistics
University of California Los Angeles Bridging the Gap Between Tools for Learning and for Doing Statistics A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Statistics by Amelia Ahlers McNamara 2015 c Copyright by Amelia Ahlers McNamara 2015 Abstract of the Dissertation Bridging the Gap Between Tools for Learning and for Doing Statistics by Amelia Ahlers McNamara Doctor of Philosophy in Statistics University of California, Los Angeles, 2015 Professor Robert L Gould, Co-chair Professor Fredrick R Paik Schoenberg, Co-chair Computers have changed the way we think about data and data analysis. While statistical programming tools have attempted to keep pace with these develop- ments, there is room for improvement in interactivity, randomization methods, and reproducible research. In addition, as in many disciplines, statistical novices tend to have a reduced experience of the true practice. This dissertation discusses the gap between tools for teaching statistics (like TinkerPlots, Fathom, and web applets) and tools for doing statistics (like SAS, SPSS, or R). We posit this gap should not exist, and provide some suggestions for bridging it. Methods for this bridge can be curricular or technological, although this work focuses primarily on the technological. We provide a list of attributes for a modern data analysis tool to support novices through the entire learning-to-doing trajectory. These attributes include easy entry for novice users, data as a first-order persistent object, support for a cycle of exploratory and confirmatory analysis, flexible plot creation, support for randomization throughout, interactivity at every level, inherent visual documenta- tion, simple support for narrative, publishing, and reproducibility, and flexibility ii to build extensions. -
On the State of Computing in Statistics Education: Tools for Learning And
On the State of Computing in Statistics Education: Tools for Learning and for Doing Amelia McNamara Smith College 1. INTRODUCTION When Rolf Biehler wrote his 1997 paper, “Software for Learning and for Doing Statistics,” some edu- cators were already using computers in their introductory statistics classes (Biehler 1997). Biehler’s paper laid out suggestions for the conscious improvement of software for statistics, and much of his vision has been realized. But, computers have improved tremendously since 1997, and statistics and data have changed along with them. It has become normative to use computers in statistics courses– the 2005 Guidelines for Assessment and Instruction in Statistics Education (GAISE) college report suggested that students “Use real data”and“Use technology for developing conceptual understanding and analyzing data”(Aliaga et al. 2005). In 2010, Deb Nolan and Duncan Temple Lang argued students should “Compute with data in the practice of statistics” (Nolan and Temple Lang 2010). Indeed, much of the hype around ‘data science’ seems to be centering around computational statistics. Donoho’s vision of ‘Greater Data Science’ is almost entirely dependent on computation (Donoho 2015). The 2016 GAISE college report updated their recommendations to “Integrate real data with a context and purpose” and “Use technology to explore concepts and analyze data” (Carver et al. 2016). So, it is clear that we need to be engaging students in statistical computing. But how? To begin, we should consider how computers are currently being used in statistics classes. Once we have a solid foundation of the current state of computation in statistics education, we can begin to dream about the future. -
Data Analyst and Evaluator
Pierce County Classification Description Data Analyst and Evaluator Department: Human Services FLSA: Non-Exempt Job Class #: 335100 Represented: No Pay Range: Professional 39 Classification descriptions are intended to present a descriptive list of the range of duties performed by employees in this class and are not intended to reflect all duties performed within the job. GENERAL FUNCTION: This is a lead worker position. Incumbents in this position play a critical role in leading the Homeless Program towards becoming data-driven, with the goal of helping our community better understand homelessness, how it can become rare, brief and a one-time occurrence. Incumbents will take lead on translating an array of data points into easy-to-understand visuals, including interactive dashboards. ESSENTIAL FUNCTIONS: Lead the manipulation, extraction, and processing of large data sets using analytical tools such as Tableau, Qlik, or other similar software. Independently analyze data by applying appropriate data analytics, qualitative and quantitative techniques, using internal and external data sets. Lead the design and maintenance of data visualizations that are easily understood by different audiences (elected officials, funders, partners, providers, as well as other internal and external partners). Clearly and succinctly distill complex information into key themes for use in a variety of communications materials. Lead the development of clear, impactful data-focused reports for various audiences that clearly communicate analysis of outputs/outcomes of the Homeless Crisis Response System. Lead internal capacity building to use data to inform strategy, communications, and investment-level decisions. Use outcome data to inform Homeless Team decisions regarding system and program level improvements, including refinements of existing programs and new program development. -
Information to Users
INFORMATION TO USERS This manuscript has been reproduced from the microfilm master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may be from any type of computer printer. The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedthrough, substandard margins, and improper alignment can adversely affect reproduction. In the unlikely event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion. Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and continuing from left to right in equal sections with small overlaps. Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6" x 9* black and white photographic prints are available for any photographs or illustrations appearing in this copy for an additional charge. Contact UMtdirectty to order. ProQuest Information and Learning 300 North Zeeb Road, Ann Arbor, Ml 48106-1346 USA 800-521-0600 UMI i r SPATIAL ASSOCIATION MEASURES FOR AN ESDA-GIS FRAMEWORK: DEVELOPMENTS, SIGNMCANCE TESTS, AND APPLICATIONS TO SPATIO-TEMPORAL INCOME DYNAMICS OF U.S. LABOR MARKET AREAS, 1969-1999 DISSERTATION Presented in Partial Fulfillment of the Requirements for The Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Sang-Il Lee, M.A. -
Data Desk Professional: Statistical Analysis for the Macintosh
DOCUMENT RESUME ED 309 760 IR 013 926 AUTHOR Wise, Steven L.; Kutish, Gerald W. TITLE Data Desk Professional: Statistical Analysis for the Macintosh. PUB DATE Mar 89 NOTE 10p,; Paper presented at the Annual Meeting of the American Educational Research Association (San Francisco, CA, March 25-30, 1989). PUB TYPE Book/Product Reviews (072) -- Speeches/Conference Papers (150) EDRS PRICE MF01/PC01 Plus Postage. DESCRIPTORS *Computer Software; Computer Software Reviews; *Microcomputers; *Statistical Analysis IDENTIFIERS Apple Macintosh; Data Desk Professional; *Exploratory Data Analysis ABSTRACT This review of Data Desk Professional, a statistical software package for Macintosh microcomputers, includes information on: (1) cost and the amount and allocation of memory; (2) usability (documentation quality, ease of use); (3) running programs; (4) program output (quality of graphics); (5) accuracy; and (6) user services. In conclusion, it is noted that the program is oriented toward an exploratory data analysis (EDA) approach, which encourages an open-ended analysis of data, and that the _ar is able to examine a data file in a very flexible and thorough fashion. In terms of traditional statistical analysis, however, Data Desk has a number of clear deficiencies, in that some of the programs are inflexible and incomplete. (GL) Reproductions supplied by EDRS are the best that can be made from the original document. U S DEPARTMENT OF EDUCATION Office Ot Erkicationai Research ano improyernent EDUCATIONAL RESOURCES INFORMATION CENTER IERICt 44.Tms Oocurnent has been rep, .used as received from the person or organization originating it C' Minor Changes nave beer made to improi.e reproduction Quality Points of or opinions stated in this dock., ment do not necessarily represent Ott c,a1 OEPIpos,ton or pohcy Data Desk Professional: Statistical Analysis for the Macintosh Steven L. -
How American Mass Media Framed the 2016
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by University of Missouri: MOspace DATA JOURNALISM AND DEMOCRACY: HOW AMERICAN MASS MEDIA FRAMED THE 2016 PRESIDENTIAL CAMPAIGN IN THE UNITED STATES USING DATA VISUALIZATION ____________________________________ A Thesis presented to the Faculty of the Graduate School at the University of Missouri-Columbia _______________________________________________________ In Partial Fulfillment of the Requirements for the Degree Master of Arts _____________________________________________________ by IULIIA ALIEVA Dr. Randall Smith, Thesis Supervisor MAY 2017 The undersigned, appointed by the Dean of the Graduate School, have examined the thesis entitled: DATA JOURNALISM AND DEMOCRACY: HOW AMERICAN MASS MEDIA FRAMED THE 2016 PRESIDENTIAL CAMPAIGN IN THE UNITED STATES USING DATA VISUALIZATION presented by Iuliia Alieva, a candidate for the degree of Master of Arts and hereby certify that in their opinion it is worthy of acceptance ____________________________________ Professor Randall Smith ____________________________________ Professor Yong Volz ____________________________________ Professor David Herzog ____________________________________ Professor Antonie Stam ACKNOWLEDGEMENTS Undoubtedly, the University of Missouri School of Journalism gave me an unparalleled advantage by immersing me into a new educational experience in the United States, which helped me to gain new qualifications, abilities to work in different cultural spaces and interact with professionals who can teach and inspire me into the future. With the help of the MU Journalism School Faculty, I improved my skills in data journalism and international journalism, as well as economic journalism and documentary filmmaking. I also gained experience in new technologies in the media, and I’m excited to apply my knowledge in the process of practical work in my home country.