Principles Of Managerial Statistics And Data Science
DOWNLOAD eBooks
Download Principles Of Managerial Statistics And Data Science PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Principles Of Managerial Statistics And Data Science book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Principles Of Managerial Statistics And Data Science
DOWNLOAD eBooks
Author : Roberto Rivera
language : en
Publisher: John Wiley & Sons
Release Date : 2020-02-05
Principles Of Managerial Statistics And Data Science written by Roberto Rivera and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-05 with Mathematics categories.
Introduces readers to the principles of managerial statistics and data science, with an emphasis on statistical literacy of business students Through a statistical perspective, this book introduces readers to the topic of data science, including Big Data, data analytics, and data wrangling. Chapters include multiple examples showing the application of the theoretical aspects presented. It features practice problems designed to ensure that readers understand the concepts and can apply them using real data. Over 100 open data sets used for examples and problems come from regions throughout the world, allowing the instructor to adapt the application to local data with which students can identify. Applications with these data sets include: Assessing if searches during a police stop in San Diego are dependent on driver’s race Visualizing the association between fat percentage and moisture percentage in Canadian cheese Modeling taxi fares in Chicago using data from millions of rides Analyzing mean sales per unit of legal marijuana products in Washington state Topics covered in Principles of Managerial Statistics and Data Science include:data visualization; descriptive measures; probability; probability distributions; mathematical expectation; confidence intervals; and hypothesis testing. Analysis of variance; simple linear regression; and multiple linear regression are also included. In addition, the book offers contingency tables, Chi-square tests, non-parametric methods, and time series methods. The textbook: Includes academic material usually covered in introductory Statistics courses, but with a data science twist, and less emphasis in the theory Relies on Minitab to present how to perform tasks with a computer Presents and motivates use of data that comes from open portals Focuses on developing an intuition on how the procedures work Exposes readers to the potential in Big Data and current failures of its use Supplementary material includes: a companion website that houses PowerPoint slides; an Instructor's Manual with tips, a syllabus model, and project ideas; R code to reproduce examples and case studies; and information about the open portal data Features an appendix with solutions to some practice problems Principles of Managerial Statistics and Data Science is a textbook for undergraduate and graduate students taking managerial Statistics courses, and a reference book for working business professionals.
Data Science For Business And Decision Making
DOWNLOAD eBooks
Author : Luiz Paulo Fávero
language : en
Publisher: Academic Press
Release Date : 2019-04-11
Data Science For Business And Decision Making written by Luiz Paulo Fávero and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-11 with Business & Economics categories.
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
Practical Statistics For Data Scientists
DOWNLOAD eBooks
Author : Peter Bruce
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-05-10
Practical Statistics For Data Scientists written by Peter Bruce and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-10 with Computers categories.
Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data
Data Science For Business
DOWNLOAD eBooks
Author : Foster Provost
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-07-27
Data Science For Business written by Foster Provost and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-27 with Business & Economics categories.
Annotation This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. By learning data science principles, you will understand the many data-mining techniques in use today. More importantly, these principles underpin the processes and strategies necessary to solve business problems through data mining techniques.
Managerial Analytics
DOWNLOAD eBooks
Author : Michael Watson
language : en
Publisher: Pearson Education
Release Date : 2013-11-26
Managerial Analytics written by Michael Watson and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-26 with Business & Economics categories.
The field of analytics is rapidly evolving, making it difficult for professionals and students to keep up the most current and effective applications. Managerial Analytics will help readers sort through all these new options and identify the appropriate solution. In this reference, authors Watson, Nelson and Cacioppi accurately define and identify the components of analytics and big data, giving readers the knowledge needed to effectively assess new aspects and applications. Building on this foundation, they review tools and solutions, identify the offerings best aligned to one’s requirements, and show how to tailor analytics applications to an organization’s specific needs. Drawing on extensive experience implementing, planning, and researching advanced analytics for business, the authors clearly explain all this, and more: What analytics is and isn’t: great examples of successful usage – and other examples where the term is being degraded into meaninglessness The difference between using analytics and “competing on analytics” How to get started with big data, by analyzing the most relevant data Components of analytics systems, from databases and Excel to BI systems and beyond Anticipating and overcoming “confirmation bias” and other pitfalls Understanding predictive analytics and getting the high-quality random samples necessary Applying game theory, Efficient Frontier, benchmarking, and revenue management models Implementing optimization at the small and large scale, and using it to make “automatic decisions”
Principles Of Data Management And Presentation
DOWNLOAD eBooks
Author : Dr. John P. Hoffmann
language : en
Publisher: Univ of California Press
Release Date : 2017-07-03
Principles Of Data Management And Presentation written by Dr. John P. Hoffmann and has been published by Univ of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-03 with Social Science categories.
The world is saturated with data. We are regularly presented with data in words, tables, and graphics. Students from many academic fields are now expected to be educated about data in one form or another. Yet the typical sequence of courses—introductory statistics and research methods—does not provide sufficient information about how to focus in on a research question, how to access data and work with datasets, or how to present data to various audiences. Principles of Data Management and Presentation addresses this gap. Assuming only that students have some familiarity with basic statistics and research methods, it provides a comprehensive set of principles for understanding and using data as part of a research project, including: • how to narrow a research topic to a specific research question • how to access and organize data that are useful for answering a research question • how to use software such as Stata, SPSS, and SAS to manage data • how to present data so that they convey a clear and effective message A companion website includes material to enhance the learning experience—specifically statistical software code and the datasets used in the examples, in text format as well as Stata, SPSS, and SAS formats. Visit www.ucpress.edu/go/datamanagement, Downloads tab.
Practical Statistics For Data Scientists
DOWNLOAD eBooks
Author : Peter Bruce
language : en
Publisher: O'Reilly Media
Release Date : 2020-04-10
Practical Statistics For Data Scientists written by Peter Bruce and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-10 with Computers categories.
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher-quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that "learn" from data Unsupervised learning methods for extracting meaning from unlabeled data
Statistics For Data Scientists
DOWNLOAD eBooks
Author : Maurits Kaptein
language : en
Publisher: Springer Nature
Release Date : 2022-02-02
Statistics For Data Scientists written by Maurits Kaptein and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-02 with Computers categories.
This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treatment of probability and statistical principles. Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, etc.), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science.
Practical Business Statistics
DOWNLOAD eBooks
Author : Andrew Siegel
language : en
Publisher: Academic Press
Release Date : 2011-03-04
Practical Business Statistics written by Andrew Siegel and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-04 with Mathematics categories.
Practical Business Statistics, Sixth Edition, is a conceptual , realistic, and matter-of-fact approach to managerial statistics that carefully maintains, but does not overemphasize, mathematical correctness. The book offers a deep understanding of how to learn from data and how to deal with uncertainty while promoting the use of practical computer applications. This teaches present and future managers how to use and understand statistics without an overdose of technical detail, enabling them to better understand the concepts at hand and to interpret results. The text uses excellent examples with real world data relating to the functional areas within Business such as finance, accounting, and marketing. It is well written and designed to help students gain a solid understanding of fundamental statistical principles without bogging them down with excess mathematical details. This edition features many examples and problems that have been updated with more recent data sets, and continues to use the ever-changing Internet as a data source. Supplemental materials include companion website with datasets and software. Each chapter begins with an overview, showing why the subject is important to business, and ends with a comprehensive summary, with key words, questions, problems, database exercises, projects, and cases in most chapters. This text is written for the introductory business/management statistics course offered for undergraduate students or Quantitative Methods in Management/ Analytics for Managers at the MBA level. User-friendly, lively writing style Separate writing chapter aids instructors in teaching how to explain quantitative analysis Over 200 carefully-drawn charts and graphs show how to visualize data Data mining is a theme that appears in many chapters, often featuring a large database (included on the website) of characteristics of 20,000 potential donors to a worthy cause and the amount actually given in response to a mailing Many of the examples and problems in the sixth edition have been updated with more recent data sets, and the ever-changing Internet continues to be featured as a data source Each chapter begins with an overview, showing why the subject is important to business, and ends with a comprehensive summary, with key words, questions, problems, database exercises, projects, and cases in most chapters All details are technically accurate (Professor Siegel has a PhD in Statistics from Stanford University and has given presentations on exploratory data analysis with its creator) while the book concentrates on the understanding and use of statistics by managers Features that have worked well for students and instructors in the first five editions have been retained
Business Analytics Principles Concepts And Applications
DOWNLOAD eBooks
Author : Marc J. Schniederjans
language : en
Publisher: Pearson Education
Release Date : 2014-04-23
Business Analytics Principles Concepts And Applications written by Marc J. Schniederjans and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-23 with Business & Economics categories.
Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of IBM's menu-based SPSS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. A valuable resource for all beginning-to-intermediate-level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.