Applied Statistics And Data Science
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Statistics For Technology
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Author : Christopher Chatfield
language : en
Publisher: Chapman & Hall
Release Date : 1978
Statistics For Technology written by Christopher Chatfield and has been published by Chapman & Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Mathematics categories.
One of the most popular introductory texts in its field, Statistics for Technology: A Course in Applied Studies presents the range of statistical methods commonly used in science, social science, and engineering.The mathematics are simple and straightforward; statistical concepts are explained carefully; and real-life (rather than contrived) examples are used throughout the chapters.Divided into three parts, the Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the planning and procedures of experiments, quality control, and life testing.Revised throughout, this Third Edition places a higher priority on the role of computers in analysis, and many new references have been incorporated. A new appendix describes general methods of tackling statistical problems, including guidance on literature searching and report writing.
Mastering Applied Statistics In Data Science
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Author : Husn Ara
language : en
Publisher: Independently Published
Release Date : 2024-04-05
Mastering Applied Statistics In Data Science written by Husn Ara and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-05 with Social Science categories.
"Mastering Applied Statistics in Data Science" offers a comprehensive guide to understanding and applying statistical methods in the field of data science. This book covers essential statistical concepts, techniques, and tools, providing readers with the knowledge and skills needed to analyze data effectively, make informed decisions, and derive actionable insights. Starting with foundational concepts such as descriptive statistics, probability theory, and inferential statistics, this book gradually progresses to more advanced topics such as regression analysis, hypothesis testing, and multivariate analysis. Each concept is explained in a clear and concise manner, with real-world examples and practical applications to illustrate its relevance in data science. Readers will learn how to: Explore and visualize data using descriptive statistics, histograms, and boxplots. Understand probability distributions and their role in statistical modeling. Conduct hypothesis tests to make inferences about population parameters. Build predictive models using regression analysis and machine learning algorithms. Analyze relationships between multiple variables using correlation and regression techniques. Apply advanced statistical methods such as time series analysis, factor analysis, and cluster analysis. Throughout the book, emphasis is placed on hands-on learning, with practical exercises and examples provided to reinforce key concepts. Whether you are a beginner looking to build a solid foundation in applied statistics or an experienced data scientist seeking to deepen your understanding of statistical methods, "Mastering Applied Statistics in Data Science" is an indispensable resource for mastering statistical analysis in the context of data science.
Applied Statistics And Data Science
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Author : Yogendra P. Chaubey
language : en
Publisher:
Release Date : 2021
Applied Statistics And Data Science written by Yogendra P. Chaubey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This proceedings volume features top contributions in modern statistical methods from Statistics 2021 Canada, the 6th Annual Canadian Conference in Applied Statistics, held virtually on July 15-18, 2021. Papers are contributed from established and emerging scholars, covering cutting-edge and contemporary innovative techniques in statistics and data science. Major areas of contribution include Bayesian statistics; computational statistics; data science; semi-parametric regression; and stochastic methods in biology, crop science, ecology and engineering. It will be a valuable edited collection for graduate students, researchers, and practitioners in a wide array of applied statistical and data science methods.
Data Science Careers Training And Hiring
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Author : Renata Rawlings-Goss
language : en
Publisher: Springer
Release Date : 2019-08-02
Data Science Careers Training And Hiring written by Renata Rawlings-Goss and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-02 with Education categories.
This book is an information packed overview of how to structure a data science career, a data science degree program, and how to hire a data science team, including resources and insights from the authors experience with national and international large-scale data projects as well as industry, academic and government partnerships, education, and workforce. Outlined here are tips and insights into navigating the data ecosystem as it currently stands, including career skills, current training programs, as well as practical hiring help and resources. Also, threaded through the book is the outline of a data ecosystem, as it could ultimately emerge, and how career seekers, training programs, and hiring managers can steer their careers, degree programs, and organizations to align with the broader future of data science. Instead of riding the current wave, the author ultimately seeks to help professionals, programs, and organizations alike prepare a sustainable plan for growth in this ever-changing world of data. The book is divided into three sections, the first “Building Data Careers”, is from the perspective of a potential career seeker interested in a career in data, the second “Building Data Programs” is from the perspective of a newly forming data science degree or training program, and the third “Building Data Talent and Workforce” is from the perspective of a Data and Analytics Hiring Manager. Each is a detailed introduction to the topic with practical steps and professional recommendations. The reason for presenting the book from different points of view is that, in the fast-paced data landscape, it is helpful to each group to more thoroughly understand the desires and challenges of the other. It will, for example, help the career seekers to understand best practices for hiring managers to better position themselves for jobs. It will be invaluable for data training programs to gain the perspective of career seekers, who they want to help and attract as students. Also, hiring managers will not only need data talent to hire, but workforce pipelines that can only come from partnerships with universities, data training programs, and educational experts. The interplay gives a broader perspective from which to build.
Applied Statistics For Social And Management Sciences
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Author : Abdul Quader Miah
language : en
Publisher: Springer
Release Date : 2016-02-29
Applied Statistics For Social And Management Sciences written by Abdul Quader Miah and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-02-29 with Social Science categories.
This book addresses the application of statistical techniques and methods across a wide range of disciplines. While its main focus is on the application of statistical methods, theoretical aspects are also provided as fundamental background information. It offers a systematic interpretation of results often discovered in general descriptions of methods and techniques such as linear and non-linear regression. SPSS is also used in all the application aspects. The presentation of data in the form of tables and graphs throughout the book not only guides users, but also explains the statistical application and assists readers in interpreting important features. The analysis of statistical data is presented consistently throughout the text. Academic researchers, practitioners and other users who work with statistical data will benefit from reading Applied Statistics for Social and Management Sciences.
Data Visualization And Statistical Literacy For Open And Big Data
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Author : Prodromou, Theodosia
language : en
Publisher: IGI Global
Release Date : 2017-03-20
Data Visualization And Statistical Literacy For Open And Big Data written by Prodromou, Theodosia and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-20 with Computers categories.
Data visualization has emerged as a serious scholarly topic, and a wide range of tools have recently been developed at an accelerated pace to aid in this research area. Examining different ways of analyzing big data can result in increased efficiency for many corporations and organizations. Data Visualization and Statistical Literacy for Open and Big Data highlights methodological developments in the way that data analytics is both learned and taught. Featuring extensive coverage on emerging relevant topics such as data complexity, statistics education, and curriculum development, this publication is geared toward teachers, academicians, students, engineers, professionals, and researchers that are interested in expanding their knowledge of data examination and analysis.
Big Data And Data Science
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Author : Dhaanyalakshmi Ahuja
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Big Data And Data Science written by Dhaanyalakshmi Ahuja and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Big Data and Data Science: Analytics for the Future dives into the fundamentals of big data and data science. We explain the data science life cycle and its major components, such as statistics and visualization, using various programming languages like R. As technology evolves, the significance of data science and big data analytics continues to grow, making this field increasingly important. Our book is designed in a reader-friendly manner, targeting newcomers to data science. Concepts are presented clearly and can be easily implemented through the procedures and algorithms provided. As data collection multiplies exponentially, analytics remains an evolving field with vast career opportunities. We cater to two types of readers: those skeptical about the benefits of big data and predictive analytics, and enthusiasts keen to explore current applications of these technologies. Big data is a fantastic choice for launching a career in IT, and this book equips you with the knowledge needed to succeed. We cover a broad spectrum of topics, ensuring a strong foundation in data science and big data analytics.
Analytics And Knowledge Management
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Author : Suliman Hawamdeh
language : en
Publisher: CRC Press
Release Date : 2018-08-06
Analytics And Knowledge Management written by Suliman Hawamdeh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-06 with Computers categories.
The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics technique. Analytics and Knowledge Management examines the role of analytics in knowledge management and the integration of big data theories, methods, and techniques into an organizational knowledge management framework. Its chapters written by researchers and professionals provide insight into theories, models, techniques, and applications with case studies examining the use of analytics in organizations. The process of transforming data into actionable knowledge is a complex process that requires the use of powerful machines and advanced analytics techniques. Analytics, on the other hand, is the examination, interpretation, and discovery of meaningful patterns, trends, and knowledge from data and textual information. It provides the basis for knowledge discovery and completes the cycle in which knowledge management and knowledge utilization happen. Organizations should develop knowledge focuses on data quality, application domain, selecting analytics techniques, and on how to take actions based on patterns and insights derived from analytics. Case studies in the book explore how to perform analytics on social networking and user-based data to develop knowledge. One case explores analyze data from Twitter feeds. Another examines the analysis of data obtained through user feedback. One chapter introduces the definitions and processes of social media analytics from different perspectives as well as focuses on techniques and tools used for social media analytics. Data visualization has a critical role in the advancement of modern data analytics, particularly in the field of business intelligence and analytics. It can guide managers in understanding market trends and customer purchasing patterns over time. The book illustrates various data visualization tools that can support answering different types of business questions to improve profits and customer relationships. This insightful reference concludes with a chapter on the critical issue of cybersecurity. It examines the process of collecting and organizing data as well as reviewing various tools for text analysis and data analytics and discusses dealing with collections of large datasets and a great deal of diverse data types from legacy system to social networks platforms.
Learn R For Applied Statistics
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Author : Eric Goh Ming Hui
language : en
Publisher: Apress
Release Date : 2018-11-30
Learn R For Applied Statistics written by Eric Goh Ming Hui and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-30 with Computers categories.
Gain the R programming language fundamentals for doing the applied statistics useful for data exploration and analysis in data science and data mining. This book covers topics ranging from R syntax basics, descriptive statistics, and data visualizations to inferential statistics and regressions. After learning R’s syntax, you will work through data visualizations such as histograms and boxplot charting, descriptive statistics, and inferential statistics such as t-test, chi-square test, ANOVA, non-parametric test, and linear regressions. Learn R for Applied Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data explorations. What You Will Learn Discover R, statistics, data science, data mining, and big data Master the fundamentals of R programming, including variables and arithmetic, vectors, lists, data frames, conditional statements, loops, and functions Work with descriptive statistics Create data visualizations, including bar charts, line charts, scatter plots, boxplots, histograms, and scatterplots Use inferential statistics including t-tests, chi-square tests, ANOVA, non-parametric tests, linear regressions, and multiple linear regressions Who This Book Is For Those who are interested in data science, in particular data exploration using applied statistics, and the use of R programming for data visualizations.
Handbook Of Methods Of Applied Statistics Planning Collection Of Data
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Author : Indra Mohan Chakravarti
language : en
Publisher:
Release Date : 1967
Handbook Of Methods Of Applied Statistics Planning Collection Of Data written by Indra Mohan Chakravarti and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1967 with Mathematical statistics categories.