Data Analysis and Decision Making in Scientific Inquiry PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Analysis and Decision Making in Scientific Inquiry PDF full book. Access full book title Data Analysis and Decision Making in Scientific Inquiry by Robert E. Landsman. Download full books in PDF and EPUB format.
Author: Robert E. Landsman
Publisher: ANOVA Science Publishing
ISBN: 0976655101
Category : Decision making
Languages : en
Pages : 244
Get Book
Book Description
Author: Robert E. Landsman
Publisher: ANOVA Science Publishing
ISBN: 0976655101
Category : Decision making
Languages : en
Pages : 244
Get Book
Book Description
Author: Robert E. Landsman
Publisher: ANOVA Science Publishing
ISBN: 097665511X
Category : Science
Languages : en
Pages : 370
Get Book
Book Description
Author: Luiz Paulo Fávero
Publisher: Academic Press
ISBN: 0128112174
Category : Business & Economics
Languages : en
Pages : 1240
Get Book
Book Description
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs
Author: Éloi Bossé
Publisher: Springer
ISBN: 303003643X
Category : Computers
Languages : en
Pages : 620
Get Book
Book Description
This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is. By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.
Author: James E. Sallis
Publisher: Springer Nature
ISBN: 3030844218
Category : Business & Economics
Languages : en
Pages : 263
Get Book
Book Description
This introductory textbook presents research methods and data analysis tools in non-technical language. It explains the research process and the basics of qualitative and quantitative data analysis, including procedures and methods, analysis, interpretation, and applications using hands-on data examples in QDA Miner Lite and IBM SPSS Statistics software. The book is divided into four parts that address study and research design; data collection, qualitative methods and surveys; statistical methods, including hypothesis testing, regression, cluster and factor analysis; and reporting. The intended audience is business and social science students learning scientific research methods, however, given its business context, the book will be equally useful for decision-makers in businesses and organizations.
Author: Jeffrey C. Bauer
Publisher: Productivity Press
ISBN: 9781138469839
Category :
Languages : en
Pages : 160
Get Book
Book Description
Americans are bombarded with statistical data each and every day, and healthcare professionals are no exception. All segments of healthcare rely on data provided by insurance companies, consultants, research firms, and the federal government to help them make a host of decisions regarding the delivery of medical services. But while these health professionals rely on data, do they really make the best use of the information? Not if they fail to understand whether the assumptions behind the formulas generating the numbers make sense. Not if they don�t understand that the world of healthcare is flooded with inaccurate, misleading, and even dangerous statistics. Statistical Analysis for Decision Makers in Healthcare: Understanding and Evaluating Critical Information in a Competitive Market, Second Edition explains the fundamental concepts of statistics, as well as their common uses and misuses. Without jargon or mathematical formulas, nationally renowned healthcare expert and author, Jeff Bauer, presents a clear verbal and visual explanation of what statistics really do. He provides a practical discussion of scientific methods and data to show why statistics should never be allowed to compensate for bad science or bad data. Relying on real-world examples, Dr. Bauer stresses a conceptual understanding that empowers readers to apply a scientifically rigorous approach to the evaluation of data. With the tools he supplies, you will learn how to dismantle statistical evidence that goes against common sense. Easy to understand, practical, and even entertaining, this is the book you wish you had when you took statistics in college � and the one you are now glad to have to defend yourself against the abundance of bad studies and misinformation that might otherwise corrupt your decisions.
Author: Jeffrey C. Bauer
Publisher: CRC Press
ISBN: 1439800774
Category : Business & Economics
Languages : en
Pages : 184
Get Book
Book Description
Americans are bombarded with statistical data each and every day, and healthcare professionals are no exception. All segments of healthcare rely on data provided by insurance companies, consultants, research firms, and the federal government to help them make a host of decisions regarding the delivery of medical services. But while these health pro
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309287812
Category : Mathematics
Languages : en
Pages : 191
Get Book
Book Description
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author: S. Christian Albright
Publisher:
ISBN: 9789814834391
Category : Decision making
Languages : en
Pages : 952
Get Book
Book Description
Author: Russell L. Ackoff
Publisher: John Wiley & Sons
ISBN:
Category : Business & Economics
Languages : en
Pages : 488
Get Book
Book Description
Intended to improve the skill of the scientist in the conduct of inquiry.
