Understanding Data
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R For Data Science
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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-12
R For Data Science written by Hadley Wickham 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 2016-12-12 with Computers categories.
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Understanding Data A Guide To Statistical Methods In Medical Research
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-05-20
Understanding Data A Guide To Statistical Methods In Medical Research written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-20 with Medical categories.
Master the art of statistical analysis in medical research with this comprehensive and practical guide! In the world of medical research, statistics are a powerful tool that helps researchers uncover hidden insights, draw meaningful conclusions, and make informed decisions. Whether you're a seasoned researcher or just starting out, this book provides a thorough foundation in statistical methods specifically tailored to the field of medicine. With clear explanations, real-world examples, and step-by-step instructions, this book guides you through the fundamental concepts of statistics, from descriptive statistics and probability to inferential statistics and advanced statistical techniques. It covers a wide range of topics, including: * **Hypothesis testing:** Learn how to formulate and test hypotheses, evaluate the strength of evidence, and draw valid conclusions from your data. * **Confidence intervals:** Understand the concept of confidence intervals and their role in estimating population parameters with a known degree of certainty. * **Correlation and regression:** Explore the relationship between variables and uncover patterns and trends in your data using correlation and regression analysis. * **Analysis of variance:** Discover how to compare multiple groups of data and identify significant differences among them using analysis of variance (ANOVA). * **Nonparametric statistics:** Delve into nonparametric statistical methods that are particularly useful when dealing with data that does not follow a normal distribution. In addition to these core statistical concepts, the book also delves into specialized statistical methods used in medical research, such as: * **Clinical trials:** Learn how to design, conduct, and analyze clinical trials to evaluate the effectiveness and safety of new treatments. * **Observational studies:** Gain insights into the relationship between risk factors and health outcomes through observational studies, such as cohort studies and case-control studies. * **Meta-analysis:** Discover how to combine the results of multiple studies to obtain a more precise and reliable estimate of the overall effect. * **Survival analysis:** Understand the methods used to analyze data related to the time it takes for an event to occur, such as disease progression or patient survival. With its comprehensive coverage, clear explanations, and practical examples, this book is an invaluable resource for researchers, students, and healthcare professionals seeking to enhance their understanding of statistical methods and their application in medical research. It empowers readers to make informed decisions, contribute to the advancement of medical knowledge, and ultimately improve patient care. If you like this book, write a review on google books!
Statistics Made Simple A Beginner S Guide To Understanding Data
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-05-15
Statistics Made Simple A Beginner S Guide To Understanding Data written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-15 with Mathematics categories.
Embark on a Statistical Odyssey with "Statistics Made Simple: A Beginner's Guide to Understanding Data" In an era where data permeates every aspect of our lives, "Statistics Made Simple" emerges as an indispensable guide for navigating the vast ocean of information that surrounds us. This comprehensive book is designed to transform you from a statistical novice into a confident data explorer, empowering you to make informed decisions and uncover hidden insights. Within these pages, you'll embark on a journey through the captivating world of statistics, where abstract concepts are transformed into practical tools for understanding the world around us. Discover the secrets of probability, the language of uncertainty, and learn how to draw meaningful conclusions from seemingly random events. Delve into the realm of descriptive statistics, where we unveil the secrets of data organization, presentation, and interpretation. Understand the significance of measures of central tendency, variability, shape, and association, and gain the skills to present data in a clear and compelling manner. But statistics is not just about describing data; it's also about making inferences and drawing conclusions. In this book, you'll master the art of inferential statistics, learning how to test hypotheses, construct confidence intervals, and conduct regression analysis. Unlock the power of statistical tools to make informed predictions and reliable generalizations. Beyond the theoretical foundations, "Statistics Made Simple" takes you on a tour of the vielfältige applications of statistics across various fields. Explore how statistics revolutionizes business, finance, healthcare, education, and countless other domains. Discover the hidden patterns and relationships that drive human behavior, economic trends, and natural phenomena. As we venture into the future of statistics, we encounter the exciting convergence of cutting-edge technologies like artificial intelligence and big data analytics. Learn how these advancements are transforming the way we collect, analyze, and interpret data, opening up new possibilities for data-driven decision-making. With its clear explanations, engaging examples, and comprehensive coverage, "Statistics Made Simple" is the ultimate companion for anyone seeking to master the language of data. Whether you're a student, a professional, or simply someone curious about the world around you, this book will equip you with the statistical skills and knowledge to navigate the complexities of the 21st century. If you like this book, write a review on google books!
The Art Of Statistical Analysis Understanding Data With Spss
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-25
The Art Of Statistical Analysis Understanding Data With Spss written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-25 with Science categories.
Embark on a data exploration journey with "The Art of Statistical Analysis: Understanding Data with SPSS," your ultimate guide to mastering statistical analysis and unlocking the power of data. Written in a clear and engaging style, this comprehensive book caters to readers of all levels, from students and researchers to business professionals and policymakers. Within these pages, you will delve into the realm of statistics, gaining a solid understanding of fundamental concepts and techniques. Discover how to organize, summarize, and interpret data effectively using descriptive statistics. Progress into inferential statistics, learning to test hypotheses, draw conclusions from samples, and make informed decisions based on data. Unleash the power of regression analysis to uncover relationships between variables and make accurate predictions. Delve into non-parametric statistics, a valuable tool for analyzing data without stringent assumptions. Explore advanced statistical techniques such as time series analysis, factor analysis, cluster analysis, and discriminant analysis to uncover hidden patterns, group similar observations, and classify data points with precision. "The Art of Statistical Analysis" goes beyond theoretical explanations, providing numerous real-world examples and step-by-step instructions to illustrate the practical applications of statistical analysis. Each chapter concludes with a summary of key points and exercises to reinforce learning and assess understanding. Whether you are a novice seeking to embark on a journey into the world of statistical analysis or a seasoned professional looking to expand your knowledge, this book is an invaluable resource. Gain the skills and insights necessary to navigate the ever-evolving landscape of data analysis and make informed decisions based on solid statistical evidence. With "The Art of Statistical Analysis: Understanding Data with SPSS," you hold the key to unlocking the secrets hidden within data. Transform raw information into actionable insights and make data-driven decisions that drive success. If you like this book, write a review on google books!
Adverse Impact Analysis
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Author : Scott B. Morris
language : en
Publisher: Psychology Press
Release Date : 2016-12-01
Adverse Impact Analysis written by Scott B. Morris and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-01 with Business & Economics categories.
Compliance with federal equal employment opportunity regulations, including civil rights laws and affirmative action requirements, requires collection and analysis of data on disparities in employment outcomes, often referred to as adverse impact. While most human resources (HR) practitioners are familiar with basic adverse impact analysis, the courts and regulatory agencies are increasingly relying on more sophisticated methods to assess disparities. Employment data are often complicated, and can include a broad array of employment actions (e.g., selection, pay, promotion, termination), as well as data that span multiple protected groups, settings, and points in time. In the era of "big data," the HR analyst often has access to larger and more complex data sets relevant to employment disparities. Consequently, an informed HR practitioner needs a richer understanding of the issues and methods for conducting disparity analyses. This book brings together the diverse literature on disparity analysis, spanning work from statistics, industrial/organizational psychology, human resource management, labor economics, and law, to provide a comprehensive and integrated summary of current best practices in the field. Throughout, the description of methods is grounded in the legal context and current trends in employment litigation and the practices of federal regulatory agencies. The book provides guidance on all phases of disparity analysis, including: How to structure diverse and complex employment data for disparity analysis How to conduct both basic and advanced statistical analyses on employment outcomes related to employee selection, promotion, compensation, termination, and other employment outcomes How to interpret results in terms of both practical and statistical significance Common practical challenges and pitfalls in disparity analysis and strategies to deal with these issues
Understanding Big Data Analytics For Enterprise Class Hadoop And Streaming Data
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Author : Paul Zikopoulos
language : en
Publisher: McGraw Hill Professional
Release Date : 2011-10-22
Understanding Big Data Analytics For Enterprise Class Hadoop And Streaming Data written by Paul Zikopoulos and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-22 with Computers categories.
Big Data represents a new era in data exploration and utilization, and IBM is uniquely positioned to help clients navigate this transformation. This book reveals how IBM is leveraging open source Big Data technology, infused with IBM technologies, to deliver a robust, secure, highly available, enterprise-class Big Data platform. The three defining characteristics of Big Data--volume, variety, and velocity--are discussed. You'll get a primer on Hadoop and how IBM is hardening it for the enterprise, and learn when to leverage IBM InfoSphere BigInsights (Big Data at rest) and IBM InfoSphere Streams (Big Data in motion) technologies. Industry use cases are also included in this practical guide. Learn how IBM hardens Hadoop for enterprise-class scalability and reliability Gain insight into IBM's unique in-motion and at-rest Big Data analytics platform Learn tips and tricks for Big Data use cases and solutions Get a quick Hadoop primer
Big Data
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Author : Bill Schmarzo
language : en
Publisher: John Wiley & Sons
Release Date : 2013-10-07
Big Data written by Bill Schmarzo 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 2013-10-07 with Business & Economics categories.
Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.
Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry
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Author : Kingshuk Srivastava
language : en
Publisher: CRC Press
Release Date : 2023-11-20
Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry written by Kingshuk Srivastava and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-20 with Technology & Engineering categories.
This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.
Understanding Data
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Author : B Erickson
language : en
Publisher: McGraw-Hill Education (UK)
Release Date : 1992-09-16
Understanding Data written by B Erickson and has been published by McGraw-Hill Education (UK) this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-09-16 with Social Science categories.
For statistics to be used by sociologists, and especially by students of sociology, they must first be easy to understand and use. Accordingly this book is aimed at that legion of professional sociologists and students who have always feared numbers; it employs much visual display, for example, as an easy way into the data. Also, the book is written in a relaxed and enthusiastic way that reassures apprehensive students without watering down what they must be taught. Classical statistics were developed to meet the requirements of the natural sciences; as such they reflect the more deductive nature of hypothesis development in these sciences. However, they have offered the sociologists little in the way of techniques for exploring messy data in the context of incomplete theories. This book attempts to remedy those weaknesses, and it emphasizes exploratory data techniques which sociologists will find useful in their day-to-day research. The primary characteristics of exploratory techniques discussed by the authors are simplicity, resistance and elucidation. Its coverage is from basic statistics up to multiple regression and two-way anova. The inter-relationship between exploratory and confirmatory techniques is stressed, and, through the alternating presentation of each, the students learn to master data analysis: to be and to feel in control.
Python Data Science Handbook
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Author : Jake VanderPlas
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-11-21
Python Data Science Handbook written by Jake VanderPlas 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 2016-11-21 with Computers categories.
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms