A Practical Guide To Scientific Data Analysis

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A Practical Guide to Scientific Data Analysis

David J. Livingstone
A Practical Guide to Scientific Data Analysis Book PDF

Author : David J. Livingstone
Publisher : John Wiley & Sons
Page : 358 pages
File Size : 41,8 Mb
Release : 2009-12-10
Category : Science
ISBN : 9780470684818

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A Practical Guide to Scientific Data Analysis by David J. Livingstone Pdf

Inspired by the author's need for practical guidance in the processes of data analysis, A Practical Guide to Scientific Data Analysis has been written as a statistical companion for the working scientist. This handbook of data analysis with worked examples focuses on the application of mathematical and statistical techniques and the interpretation of their results. Covering the most common statistical methods for examining and exploring relationships in data, the text includes extensive examples from a variety of scientific disciplines. The chapters are organised logically, from planning an experiment, through examining and displaying the data, to constructing quantitative models. Each chapter is intended to stand alone so that casual users can refer to the section that is most appropriate to their problem. Written by a highly qualified and internationally respected author this text: Presents statistics for the non-statistician Explains a variety of methods to extract information from data Describes the application of statistical methods to the design of “performance chemicals” Emphasises the application of statistical techniques and the interpretation of their results Of practical use to chemists, biochemists, pharmacists, biologists and researchers from many other scientific disciplines in both industry and academia.

Making Sense of Data I

Glenn J. Myatt,Wayne P. Johnson
Making Sense of Data I Book PDF

Author : Glenn J. Myatt,Wayne P. Johnson
Publisher : John Wiley & Sons
Page : 262 pages
File Size : 54,5 Mb
Release : 2014-07-02
Category : Mathematics
ISBN : 9781118422106

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Making Sense of Data I by Glenn J. Myatt,Wayne P. Johnson Pdf

Praise for the First Edition “...a well-written book on data analysis and data mining that provides an excellent foundation...” —CHOICE “This is a must-read book for learning practical statistics and data analysis...” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available TraceisTM software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.

Data Analysis for Social Science

Elena Llaudet,Kosuke Imai
Data Analysis for Social Science Book PDF

Author : Elena Llaudet,Kosuke Imai
Publisher : Princeton University Press
Page : 256 pages
File Size : 45,8 Mb
Release : 2022-11-29
Category : Computers
ISBN : 9780691199436

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Data Analysis for Social Science by Elena Llaudet,Kosuke Imai Pdf

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Applied Longitudinal Data Analysis for Medical Science

Jos W. R. Twisk
Applied Longitudinal Data Analysis for Medical Science Book PDF

Author : Jos W. R. Twisk
Publisher : Cambridge University Press
Page : 271 pages
File Size : 41,9 Mb
Release : 2023-05-31
Category : Medical
ISBN : 9781009288040

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Applied Longitudinal Data Analysis for Medical Science by Jos W. R. Twisk Pdf

Discusses methods available for longitudinal data analysis in non-technical language, allowing readers to apply techniques easily to their work. Aimed at non-statisticians and researchers working in medical science and utilising longitudinal studies, the interpretation of the results of various methods of analysis is emphasised.

Practical Statistics for Data Scientists

Peter Bruce,Andrew Bruce
Practical Statistics for Data Scientists Book PDF

Author : Peter Bruce,Andrew Bruce
Publisher : "O'Reilly Media, Inc."
Page : 395 pages
File Size : 40,6 Mb
Release : 2017-05-10
Category : Computers
ISBN : 9781491952917

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Practical Statistics for Data Scientists by Peter Bruce,Andrew Bruce Pdf

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

A Practical Guide to Using Panel Data

Simonetta Longhi,Alita Nandi
A Practical Guide to Using Panel Data Book PDF

Author : Simonetta Longhi,Alita Nandi
Publisher : SAGE
Page : 451 pages
File Size : 47,6 Mb
Release : 2014-12-01
Category : Social Science
ISBN : 9781473911338

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A Practical Guide to Using Panel Data by Simonetta Longhi,Alita Nandi Pdf

This timely, thoughtful book provides a clear introduction to using panel data in research. It describes the different types of panel datasets commonly used for empirical analysis, and how to use them for cross sectional, panel, and event history analysis. Longhi and Nandi then guide the reader through the data management and estimation process, including the interpretation of the results and the preparation of the final output tables. Using existing data sets and structured as hands-on exercises, each chapter engages with practical issues associated with using data in research. These include: Data cleaning Data preparation Computation of descriptive statistics Using sample weights Choosing and implementing the right estimator Interpreting results Preparing final output tables Graphical representation Written by experienced authors this exciting textbook provides the practical tools needed to use panel data in research.

Practical Data Analysis

Hector Cuesta,Dr. Sampath Kumar
Practical Data Analysis Book PDF

Author : Hector Cuesta,Dr. Sampath Kumar
Publisher : Packt Publishing Ltd
Page : 338 pages
File Size : 44,8 Mb
Release : 2016-09-30
Category : Computers
ISBN : 9781785286667

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Practical Data Analysis by Hector Cuesta,Dr. Sampath Kumar Pdf

A practical guide to obtaining, transforming, exploring, and analyzing data using Python, MongoDB, and Apache Spark About This Book Learn to use various data analysis tools and algorithms to classify, cluster, visualize, simulate, and forecast your data Apply Machine Learning algorithms to different kinds of data such as social networks, time series, and images A hands-on guide to understanding the nature of data and how to turn it into insight Who This Book Is For This book is for developers who want to implement data analysis and data-driven algorithms in a practical way. It is also suitable for those without a background in data analysis or data processing. Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. Data analysis involves asking many questions about data in order to discover insights and generate value for a product or a service. This book explains the basic data algorithms without the theoretical jargon, and you'll get hands-on turning data into insights using machine learning techniques. We will perform data-driven innovation processing for several types of data such as text, Images, social network graphs, documents, and time series, showing you how to implement large data processing with MongoDB and Apache Spark. Style and approach This is a hands-on guide to data analysis and data processing. The concrete examples are explained with simple code and accessible data.

Making Sense of Data

Glenn J. Myatt
Making Sense of Data Book PDF

Author : Glenn J. Myatt
Publisher : John Wiley & Sons
Page : 294 pages
File Size : 51,8 Mb
Release : 2007-02-26
Category : Mathematics
ISBN : 9780470101018

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Making Sense of Data by Glenn J. Myatt Pdf

A practical, step-by-step approach to making sense out of data Making Sense of Data educates readers on the steps and issues that need to be considered in order to successfully complete a data analysis or data mining project. The author provides clear explanations that guide the reader to make timely and accurate decisions from data in almost every field of study. A step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. With a comprehensive collection of methods from both data analysis and data mining disciplines, this book successfully describes the issues that need to be considered, the steps that need to be taken, and appropriately treats technical topics to accomplish effective decision making from data. Readers are given a solid foundation in the procedures associated with complex data analysis or data mining projects and are provided with concrete discussions of the most universal tasks and technical solutions related to the analysis of data, including: * Problem definitions * Data preparation * Data visualization * Data mining * Statistics * Grouping methods * Predictive modeling * Deployment issues and applications Throughout the book, the author examines why these multiple approaches are needed and how these methods will solve different problems. Processes, along with methods, are carefully and meticulously outlined for use in any data analysis or data mining project. From summarizing and interpreting data, to identifying non-trivial facts, patterns, and relationships in the data, to making predictions from the data, Making Sense of Data addresses the many issues that need to be considered as well as the steps that need to be taken to master data analysis and mining.

Applied Longitudinal Data Analysis for Epidemiology

Jos W. R. Twisk
Applied Longitudinal Data Analysis for Epidemiology Book PDF

Author : Jos W. R. Twisk
Publisher : Cambridge University Press
Page : 337 pages
File Size : 53,7 Mb
Release : 2013-05-09
Category : Medical
ISBN : 9781107067608

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Applied Longitudinal Data Analysis for Epidemiology by Jos W. R. Twisk Pdf

This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.

A Practical Guide To Brain Data Analysis

Vieito Joao Paulo,Da Rocha Armando Freitas,Thomaz Carlos
A Practical Guide To Brain Data Analysis Book PDF

Author : Vieito Joao Paulo,Da Rocha Armando Freitas,Thomaz Carlos
Publisher : World Scientific
Page : 204 pages
File Size : 45,6 Mb
Release : 2016-12-21
Category : Science
ISBN : 9789813144453

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A Practical Guide To Brain Data Analysis by Vieito Joao Paulo,Da Rocha Armando Freitas,Thomaz Carlos Pdf

This book was developed to help students and researchers in the fields of economics, finance, law and other social science areas to understand and apply neuroscience. With the use of neuroscience technologies, it is now possible to understand how people make decisions in practice, using friendly and ecological experimental setups. The first half of the book studies the decision-making process and explains how the brain is organized. It presents the brain as a distributed processing system, shows how to record brain activities, and how to combine neurosciences and statistical tools to design experiments. In the last chapters, experiments on stock market decision, dilemma judgment, vote decision and understanding of media propaganda are described and discussed.

Big Data Analytics

Kim H. Pries,Robert Dunnigan
Big Data Analytics Book PDF

Author : Kim H. Pries,Robert Dunnigan
Publisher : CRC Press
Page : 576 pages
File Size : 50,5 Mb
Release : 2015-02-05
Category : Computers
ISBN : 9781482234527

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Big Data Analytics by Kim H. Pries,Robert Dunnigan Pdf

With this book, managers and decision makers are given the tools to make more informed decisions about big data purchasing initiatives. Big Data Analytics: A Practical Guide for Managers not only supplies descriptions of common tools, but also surveys the various products and vendors that supply the big data market.Comparing and contrasting the dif

Eddy Covariance

Marc Aubinet,Timo Vesala,Dario Papale
Eddy Covariance Book PDF

Author : Marc Aubinet,Timo Vesala,Dario Papale
Publisher : Springer Science & Business Media
Page : 451 pages
File Size : 45,8 Mb
Release : 2012-01-18
Category : Science
ISBN : 9789400723504

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Eddy Covariance by Marc Aubinet,Timo Vesala,Dario Papale Pdf

This highly practical handbook is an exhaustive treatment of eddy covariance measurement that will be of keen interest to scientists who are not necessarily specialists in micrometeorology. The chapters cover measuring fluxes using eddy covariance technique, from the tower installation and system dimensioning to data collection, correction and analysis. With a state-of-the-art perspective, the authors examine the latest techniques and address the most up-to-date methods for data processing and quality control. The chapters provide answers to data treatment problems including data filtering, footprint analysis, data gap filling, uncertainty evaluation, and flux separation, among others. The authors cover the application of measurement techniques in different ecosystems such as forest, crops, grassland, wetland, lakes and rivers, and urban areas, highlighting peculiarities, specific practices and methods to be considered. The book also covers what to do when you have all your data, summarizing the objectives of a database as well as using case studies of the CarboEurope and FLUXNET databases to demonstrate the way they should be maintained and managed. Policies for data use, exchange and publication are also discussed and proposed. This one compendium is a valuable source of information on eddy covariance measurement that allows readers to make rational and relevant choices in positioning, dimensioning, installing and maintaining an eddy covariance site; collecting, treating, correcting and analyzing eddy covariance data; and scaling up eddy flux measurements to annual scale and evaluating their uncertainty.

Introduction to Data Science

Rafael A. Irizarry
Introduction to Data Science Book PDF

Author : Rafael A. Irizarry
Publisher : CRC Press
Page : 794 pages
File Size : 47,6 Mb
Release : 2019-11-20
Category : Mathematics
ISBN : 9781000708035

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Introduction to Data Science by Rafael A. Irizarry Pdf

Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.

A Practical Guide to Data Analysis Using R

John H. Maindonald,W. John Braun,Jeffrey L. Andrews
A Practical Guide to Data Analysis Using R Book PDF

Author : John H. Maindonald,W. John Braun,Jeffrey L. Andrews
Publisher : Cambridge University Press
Page : 552 pages
File Size : 53,9 Mb
Release : 2024-05-31
Category : Computers
ISBN : 9781009282260

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A Practical Guide to Data Analysis Using R by John H. Maindonald,W. John Braun,Jeffrey L. Andrews Pdf

Using diverse real-world examples, this text examines what models used for data analysis mean in a specific research context. What assumptions underlie analyses, and how can you check them? Building on the successful 'Data Analysis and Graphics Using R,' 3rd edition (Cambridge, 2010), it expands upon topics including cluster analysis, exponential time series, matching, seasonality, and resampling approaches. An extended look at p-values leads to an exploration of replicability issues and of contexts where numerous p-values exist, including gene expression. Developing practical intuition, this book assists scientists in the analysis of their own data, and familiarizes students in statistical theory with practical data analysis. The worked examples and accompanying commentary teach readers to recognize when a method works and, more importantly, when it doesn't. Each chapter contains copious exercises. Selected solutions, notes, slides, and R code are available online, with extensive references pointing to detailed guides to R.

Practical Guide to ChIP-seq Data Analysis

Borbala Mifsud,Kathi Zarnack,Anaïs F Bardet
Practical Guide to ChIP seq Data Analysis Book PDF

Author : Borbala Mifsud,Kathi Zarnack,Anaïs F Bardet
Publisher : CRC Press
Page : 100 pages
File Size : 44,9 Mb
Release : 2018-10-26
Category : Computers
ISBN : 9780429946394

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Practical Guide to ChIP-seq Data Analysis by Borbala Mifsud,Kathi Zarnack,Anaïs F Bardet Pdf

Chromatin immunoprecipitation sequencing (ChIP-seq), which maps the genome-wide localization patterns of transcription factors and epigenetic marks, is among the most widely used methods in molecular biology. Practical Guide to ChIP-seq Data Analysis will guide readers through the steps of ChIP-seq analysis: from quality control, through peak calling, to downstream analyses. It will help experimental biologists to design their ChIP-seq experiments with the analysis in mind, and to perform the basic analysis steps themselves. It also aims to support bioinformaticians to understand how the data is generated, what the sources of biases are, and which methods are appropriate for different analyses.