Applied Statistics And Data Science

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Applied Statistical Modeling And Data Analytics

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Author : Srikanta Mishra
language : en
Publisher: Elsevier
Release Date : 2017-10-27

Applied Statistical Modeling And Data Analytics written by Srikanta Mishra and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-27 with Science categories.

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. - Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains - Written by practitioners for practitioners - Presents an easy to follow narrative which progresses from simple concepts to more challenging ones - Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences - Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications

Applied Statistics For The Social And Health Sciences

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Author : Rachel A. Gordon
language : en
Publisher: Taylor & Francis
Release Date : 2023-11-15

Applied Statistics For The Social And Health Sciences written by Rachel A. Gordon and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-15 with Social Science categories.

Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards. Reflecting the growing importance of "Big Data" in the social and health sciences, this thoroughly revised and streamlined new edition covers best practice in the use of statistics in social and health sciences, draws upon new literatures and empirical examples, and highlights the importance of statistical programming, including coding, reproducibility, transparency, and open science. Key features of the book include: interweaving the teaching of statistical concepts with examples from publicly available social and health science data and literature excerpts; thoroughly integrating the teaching of statistical theory with the teaching of data access, processing, and analysis in Stata; recognizing debates and critiques of the origins and uses of quantitative methods.

Statistics And Data Analysis For Engineers And Scientists

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Author : Tanvir Mustafy
language : en
Publisher: Springer Nature
Release Date : 2024-01-10

Statistics And Data Analysis For Engineers And Scientists written by Tanvir Mustafy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-10 with Computers categories.

This textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs—Microsoft Excel, SPSS, and MATLAB. The book combining the different data analysis tools is a unique approach. The book presents a variety of real-life problems in data analysis and machine learning, delivering the best solution. Analysis methods presented in this book include but are not limited to, performing various algebraic and trigonometric operations, regression modeling, and correlation, as well as plotting graphs and charts to represent the results. Fundamental concepts of applied statistics are also explained here, with illustrative examples. Thus, this book presents a pioneering solution to help a wide range of students, researchers, and professionals learn data processing, interpret different findings derived from the analyses,and apply them to their research or professional fields. The book also includes worked examples of practical problems. The primary focus behind designing these examples is understanding the concepts of data analysis and how it can solve problems. The chapters include practice exercises to assist users in enhancing their skills to execute statistical analysis calculations using software instead of relying on tables for probabilities and percentiles in the present world.

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.

Statistics For Data Science And Policy Analysis

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Author : Azizur Rahman
language : en
Publisher: Springer Nature
Release Date : 2020-03-31

Statistics For Data Science And Policy Analysis written by Azizur Rahman and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-31 with Mathematics categories.

This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019. Written by leading international experts in the field of statistics, data science and policy evaluation. This book explores the theme of effective policy methods through the use of big data, accurate estimates and modern computing tools and statistical modelling.

An Introduction To Applied Statistics

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Author : Edward T. Vieira, Jr.
language : en
Publisher: Taylor & Francis
Release Date : 2025-06-09

An Introduction To Applied Statistics written by Edward T. Vieira, Jr. and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-09 with Education categories.

An Introduction to Applied Statistics offers a comprehensive and accessible foundation in applied statistics, empowering students with the essential concepts and practical skills necessary for data-driven decision-making in today's world. Thoroughly covering key topics – including data management, probability fundamentals, data screening, descriptive statistics, and a broad spectrum of inferential analysis techniques – this indispensable guide demystifies statistical concepts and equips students to confidently apply statistical analysis in real-world contexts. With a systematic, beginner-friendly approach, the author assumes no prior knowledge, making complex statistical foundations accessible to students from a variety of disciplines. Concise, digestible chapters build statistical competencies within a practical, evidence-based framework, minimizing technical jargon to facilitate comprehension. Now in its latest edition, the book is fully updated with SPSS v29.0 instructions and screenshots, ensuring compatibility with the most recent software developments. It also includes expanded content on addressing nonrandom sampling issues, such as case weighting, and delves into advanced topics like factor analysis, logistic regression, cluster analysis, and discriminant analysis, catering to the evolving needs of students and professionals alike. An invaluable resource for introductory quantitative research methods courses in psychology, social sciences, business, and marketing, this text combines practical examples, online resources, and an approachable format to support both learning and application. Key Features: Concise chapters integrating real-world applications: Seamlessly blends statistical skills with practical scenarios, illustrating the flexible use of statistics in evidence-based decision-making. Accessible presentation: Offers practical explanations of statistical procedures with minimal technical jargon, enhancing understanding and retention. Foundational preparation: Early chapters are designed to equip students for advanced statistical procedures, building a strong foundational knowledge. Step-by-step SPSS instructions: Provides detailed SPSS v29.0 guidance with screenshots to reinforce comprehension and hands-on skills. Real-world exercises with answers: Includes practical exercises complete with solutions to facilitate active learning and application. Comprehensive instructor resources: Offers extensive teaching support with chapter PowerPoints and test banks to enhance the educational experience.

Applied Statistics In Biology

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Author : Stephen R. Bowley
language : en
Publisher: John Wiley & Sons
Release Date : 2025-10-07

Applied Statistics In Biology written by Stephen R. Bowley 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 2025-10-07 with Mathematics categories.

Understand applied statistics and its application in biology research Biology and its related sciences generate prodigious quantities of data through experimentation and observation. Interpreting this data and using it to generate statistically defensible inferences has become one of the most significant components of modern biological research. There are, however, very few up-to-date resources by which graduate students and researchers in biology can familiarize themselves with the key methodologies of applied statistics as they specifically connect to the applied life sciences. Applied Statistics in Biology remedies this oversight with a thorough, accessible overview to statistics and its biological applications. Beginning with the history and fundamentals of statistics, it covers all major statistical modes of analysis that biologists might find useful, with an eye towards a robust quantitative education for biologists. Fully up to date and addressing all conventional approaches to statistical analysis, it’s a must-own for biology students and researchers alike. Applied Statistics in Biology readers will also find: Treatment rooted in years of graduate teaching in statistics and biology Detailed discussion of topics including regression, “non-Gaussian data,” multivariate techniques, and many more A valuable complement to existing resources on applied statistics Applied Statistics in Biology is ideal for graduate students in agriculture, biology, natural resources, and related fields, as well as for instructors and researchers in these and related subjects.

New Advances In Statistics And Data Science

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Author : Ding-Geng Chen
language : en
Publisher: Springer
Release Date : 2018-01-17

New Advances In Statistics And Data Science written by Ding-Geng Chen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-17 with Mathematics categories.

This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.

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.

Data Science And Analytics With Python R And Spss Programming

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Author : V.K. Jain
language : en
Publisher: KHANNA PUBLISHING HOUSE
Release Date :

Data Science And Analytics With Python R And Spss Programming written by V.K. Jain and has been published by KHANNA PUBLISHING HOUSE this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

The Book has been written completely as per AICTE recommended syllabus on "Data Sciences". SALIENT FEATURES OF THE BOOK: Explains how data is collected, managed and stored for data science. With complete courseware for understand the key concepts in data science including their real-world applications and the toolkit used by data scientists. Implement data collection and management. Provided with state of the arts subjectwise. With all required tutorials on R, Python and Bokeh, Anaconda, IBM SPSS-21 and Matplotlib.