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In 2011 the World Bank—with funding from the Bill and Melinda Gates Foundation—launched the Global Findex database, the world's most comprehensive data set on how adults save, borrow, make payments, and manage risk. Drawing on survey data collected in collaboration with Gallup, Inc., the Global Findex database covers more than 140 economies around the world. The initial survey round was followed by a second one in 2014 and by a third in 2017. Compiled using nationally representative surveys of more than 150,000 adults age 15 and above in over 140 economies, The Global Findex Database 2017: Measuring Financial Inclusion and the Fintech Revolution includes updated indicators on access to and use of formal and informal financial services. It has additional data on the use of financial technology (or fintech), including the use of mobile phones and the Internet to conduct financial transactions. The data reveal opportunities to expand access to financial services among people who do not have an account—the unbanked—as well as to promote greater use of digital financial services among those who do have an account. The Global Findex database has become a mainstay of global efforts to promote financial inclusion. In addition to being widely cited by scholars and development practitioners, Global Findex data are used to track progress toward the World Bank goal of Universal Financial Access by 2020 and the United Nations Sustainable Development Goals. The database, the full text of the report, and the underlying country-level data for all figures—along with the questionnaire, the survey methodology, and other relevant materials—are available at www.worldbank.org/globalfindex.
This book teaches the concepts and tools behind reporting modern data analyses in a reproducible manner. Reproducibility is the idea that data analyses should be published or made available with their data and software code so that others may verify the findings and build upon them. The need for reproducible report writing is increasing dramatically as data analyses become more complex, involving larger datasets and more sophisticated computations. Reproducibility allows for people to focus on the actual content of a data analysis, rather than on superficial details reported in a written summary. In addition, reproducibility makes an analysis more useful to others because the data and code that actually conducted the analysis are available. This book will focus on literate statistical analysis tools which allow one to publish data analyses in a single document that allows others to easily execute the same analysis to obtain the same results.
From data security company Code42, Inside Jobs offers companies of all sizes a new way to secure today’s collaborative cultures—one that works without compromising sensitive company data or slowing business down. Authors Joe Payne, Jadee Hanson, and Mark Wojtasiak, seasoned veterans in the cybersecurity space, provide a top-down and bottom-up picture of the rewards and perils involved in running and securing organizations focused on rapid, iterative, and collaborative innovation. Modern day data security can no longer be accomplished by “Big Brother” forms of monitoring or traditional prevention solutions that rely solely on classification and blocking systems. These technologies frustrate employees, impede collaboration, and force productivity work-arounds that risk the very data you need to secure. They provide the illusion that your trade secrets, customer lists, patents, and other intellectual property are protected. That couldn’t be farther from the truth, as insider threats continue to grow. These include: Well-intentioned employees inadvertently sharing proprietary data Departing employees taking your trade secrets with them to the competition A high-risk employee moving source code to an unsanctioned cloud service What’s the solution? It’s not the hunt for hooded, malicious wrongdoers that you might expect. The new world of data security is built on security acting as an ally versus an adversary. It assumes positive intent, creates organizational transparency, establishes acceptable data use policies, increases security awareness, and provides ongoing training. Whether you are a CEO, CIO, CISO, CHRO, general counsel, or business leader, this book will help you understand the important role you have to play in securing the collaborative cultures of the future.
A source for financial information on NIH programs and related federal and national activities. Contains data on health R&D costs, NIH appropriations and obligations, extramural awards, research training, NIH staff and clinical center, and national mortality and morbidity data.
Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.