Essentials Of Multivariate Data Analysis
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Essentials Of Multivariate Data Analysis
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Author : Neil H. Spencer
language : en
Publisher: CRC Press
Release Date : 2013-12-17
Essentials Of Multivariate Data Analysis written by Neil H. Spencer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-17 with Mathematics categories.
Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m
Essentials Of Data Analysis
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Author : Agasti Khatri
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Essentials Of Data Analysis written by Agasti Khatri and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
"Essentials of Data Analysis" is an indispensable guide that navigates readers through the world of data-driven decision-making. This book presents essential concepts, techniques, and tools in an accessible and user-friendly manner. It serves as a trusted companion for both beginners and professionals in their data analysis journey. We start by laying a solid foundation in data analysis principles, providing a comprehensive understanding of key concepts and methodologies. The book delves into practical techniques for data manipulation, visualization, and exploration, equipping readers with the skills to extract actionable insights from raw data. Real-world examples, case studies, and hands-on exercises bring abstract concepts to life. We emphasize the ethical and responsible use of data, guiding readers through ethical considerations, privacy concerns, and regulatory requirements. This fosters a culture of ethical awareness and accountability. Additionally, we explore emerging trends and technologies shaping the future of data analysis, such as artificial intelligence, machine learning, augmented analytics, and edge computing. By adopting innovative techniques, readers can drive meaningful change within their organizations. "Essentials of Data Analysis" is a valuable resource for enhancing analytical skills, advancing careers, and understanding the role of data in decision-making.
Essentials Of Mineral Exploration And Evaluation
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Author : S. M. Gandhi
language : en
Publisher: Elsevier
Release Date : 2016-05-10
Essentials Of Mineral Exploration And Evaluation written by S. M. Gandhi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-10 with Science categories.
Essentials of Mineral Exploration and Evaluation offers a thorough overview of methods used in mineral exploration campaigns, evaluation, reporting and economic assessment processes. Fully illustrated to cover the state-of-the-art exploration techniques and evaluation of mineral assets being practiced globally, this up-to-date reference offers balanced coverage of the latest knowledge and current global trends in successful mineral exploration and evaluation. From mineral deposits, to remote sensing, to sampling and analysis, Essentials of Mineral Exploration and Evaluation offers an extensive look at this rapidly changing field. - Covers the complete spectrum of all aspects of ore deposits and mining them, providing a "one-stop shop" for experts and students - Presents the most up-to-date information on developments and methods in all areas of mineral exploration - Includes chapters on application of GIS, statistics, and geostatistics in mineral exploration and evaluation - Includes case studies to enhance practical application of concepts
Essential First Steps To Data Analysis
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Author : Carol S. Parke
language : en
Publisher: SAGE
Release Date : 2013
Essential First Steps To Data Analysis written by Carol S. Parke and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Reference categories.
The purpose of this book is to provide instruction and guidance on preparing quantitative data sets prior to answering a study's research questions. Preparation may involve data management and manipulation tasks, data organization, structural changes to data files, or conducting preliminary analysis such as examining the scale of a variable, the validity of assumptions or the nature and extent of missing data. The oresultso from these essential first steps can also help guide a researcher in selecting the most appropriate statistical tests for his/her study. The book is intended to serve as a supplemental text in statistics or research courses offered in graduate programs in education, counseling, school psychology, behavioral sciences, and social sciences as well as undergraduate programs that contain a heavy emphasis on statistics. The content and issues covered are also beneficial for faculty and researchers who are knowledgeable about research design and able to use a statistical software package, but are unsure of the first steps to take with their data. Increasingly, faculty are forming partnerships with schools, clinics, and other institutions to help them analyze data in their extensive databases. This book can serve as a reference for helping them get existing data files in an appropriate form to run statistical analysis. This book is not a replacement for a statistics textbook. It assumes that readers have some knowledge of basic statistical concepts and use of statistical software, or that they will be learning these concepts and skills concurrently throughout the course. SPSS was chosen to illustrate the preparation, evaluation, and manipulation of data. However, students or researchers who do not use SPSS will benefit from the content since the overall structure and pedagogical approach of the book focuses heavily on the data issues and decisions to be made.
Essentials Of Research Methodology
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Author : Dr. Manu Y M
language : en
Publisher: RK Publication
Release Date : 2024-12-17
Essentials Of Research Methodology written by Dr. Manu Y M and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-17 with Science categories.
Essentials of Research Methodology the fundamental principles and techniques of conducting scientific research. Covering topics such as research design, data collection methods, statistical analysis, and ethical considerations, the provides a structured approach to systematic inquiry. It is designed to help students, scholars, and professionals develop critical research skills essential for academic and practical investigations. Emphasizing both qualitative and quantitative methods, this serves as a valuable resource for those seeking to understand the complexities of research in various disciplines.
Essentials Of Business Research
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Author : Jonathan Wilson
language : en
Publisher: SAGE
Release Date : 2010-04-20
Essentials Of Business Research written by Jonathan Wilson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-20 with Social Science categories.
Essentials of Business Research: A Guide to Doing Your Research Project is a concise, student-friendly text that cuts through the jargon of research methods terminology to present a clear guide to the basics of methodology in a business and management context. This extremely accessible book is informed throughout by the use of clear case studies and examples that serve to bring the research process to life for student readers. Unusually for a Methods text, Wilson also explicitly considers the importance of the supervisor in the dissertation process, and explains for the reader what lecturers are looking for from their students at every stage of the process in a good research project. This book aims to guide the student through the entire research process by using actual student case examples and explaining the role of the supervisor and how to meet their expectations. Key features include: - ‘You’re the Supervisor’ sections – helps students to meet their learning outcomes; - ‘Common questions and answers’ – provides students with an invaluable point of reference for some of the challenges they are likely to face while undertaking their research project; - Comprehensive section on ethical issues students need to consider when undertaking their research project; - A full student glossary. - The book is packed throughout with student-friendly features such as helpful diagrams, student case studies, chapter objectives, annotated further reading sections and summary and references at the end of each chapter. Essentials of Business Research is accompanied by a companion website containing an array of material for lecturers and students including: multiple choice questions to enable students to test their knowledge and progress; chapter-by-chapter links to academic journal articles demonstrating each method’s application; chapter-by-chapter links to youtube resources to provide further context; chapter-by-chapter powerpoint slides to help lecturers and students.
Machine Learning Essentials
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Author : Alboukadel Kassambara
language : en
Publisher: STHDA
Release Date : 2018-03-10
Machine Learning Essentials written by Alboukadel Kassambara and has been published by STHDA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-10 with Computers categories.
Discovering knowledge from big multivariate data, recorded every days, requires specialized machine learning techniques. This book presents an easy to use practical guide in R to compute the most popular machine learning methods for exploring real word data sets, as well as, for building predictive models. The main parts of the book include: A) Unsupervised learning methods, to explore and discover knowledge from a large multivariate data set using clustering and principal component methods. You will learn hierarchical clustering, k-means, principal component analysis and correspondence analysis methods. B) Regression analysis, to predict a quantitative outcome value using linear regression and non-linear regression strategies. C) Classification techniques, to predict a qualitative outcome value using logistic regression, discriminant analysis, naive bayes classifier and support vector machines. D) Advanced machine learning methods, to build robust regression and classification models using k-nearest neighbors methods, decision tree models, ensemble methods (bagging, random forest and boosting). E) Model selection methods, to select automatically the best combination of predictor variables for building an optimal predictive model. These include, best subsets selection methods, stepwise regression and penalized regression (ridge, lasso and elastic net regression models). We also present principal component-based regression methods, which are useful when the data contain multiple correlated predictor variables. F) Model validation and evaluation techniques for measuring the performance of a predictive model. G) Model diagnostics for detecting and fixing a potential problems in a predictive model. The book presents the basic principles of these tasks and provide many examples in R. This book offers solid guidance in data mining for students and researchers. Key features: - Covers machine learning algorithm and implementation - Key mathematical concepts are presented - Short, self-contained chapters with practical examples.
Python Data Science Essentials
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Author : Alberto Boschetti
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-28
Python Data Science Essentials written by Alberto Boschetti and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-28 with Computers categories.
Gain useful insights from your data using popular data science tools Key FeaturesA one-stop guide to Python libraries such as pandas and NumPyComprehensive coverage of data science operations such as data cleaning and data manipulationChoose scalable learning algorithms for your data science tasksBook Description Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You’ll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost. By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users What you will learnSet up your data science toolbox on Windows, Mac, and LinuxUse the core machine learning methods offered by the scikit-learn libraryManipulate, fix, and explore data to solve data science problemsLearn advanced explorative and manipulative techniques to solve data operationsOptimize your machine learning models for optimized performanceExplore and cluster graphs, taking advantage of interconnections and links in your dataWho this book is for If you’re a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book.
The Essentials Of Marketing Research
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Author : Lawrence S. Silver
language : en
Publisher: Routledge
Release Date : 2013
The Essentials Of Marketing Research written by Lawrence S. Silver and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Business & Economics categories.
Identifying and assessing the ways in which changes in the marketing mix affect consumer behavior is key to a successful marketing strategy. This book guides the student in designing, conducting and interpreting marketing research. This comprehensive textbook covers the full range of topics, including: Secondary research and data mining ; Internet marketing research ; Qualitative and exploratory research ; Statistical analysis and Marketing research ethics. With learning objectives at the beginning of each chapter, a host of cases and a comprehensive companion website, this book offers a range of tools to help students develop and test their research and analytical skills.
Essentials Of Bioinformatics Volume Iii
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Author : Khalid Rehman Hakeem
language : en
Publisher: Springer Nature
Release Date : 2019-11-01
Essentials Of Bioinformatics Volume Iii written by Khalid Rehman Hakeem and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-01 with Science categories.
Bioinformatics is an integrative field of computer science, genetics, genomics, proteomics, and statistics, which has undoubtedly revolutionized the study of biology and medicine in past decades. It mainly assists in modeling, predicting and interpreting large multidimensional biological data by utilizing advanced computational methods. Despite its enormous potential, bioinformatics is not widely integrated into the academic curriculum as most life science students and researchers are still not equipped with the necessary knowledge to take advantage of this powerful tool. Hence, the primary purpose of our book is to supplement this unmet need by providing an easily accessible platform for students and researchers starting their career in life sciences. This book aims to avoid sophisticated computational algorithms and programming. Instead, it will mostly focus on simple DIY analysis and interpretation of biological data with personal computers. Our belief is that once the beginners acquire these basic skillsets, they will be able to handle most of the bioinformatics tools for their research work and to better understand their experimental outcomes. The third volume is titled In Silico Life Sciences: Agriculture. It focuses on plant genetic, genomic, transcriptomic, proteomic and metabolomics data. Using examples of new crop diseases-emergence, crop productivity and biotic/abiotic stress tolerance, this book illustrates how bioinformatics can be an integral components of modern day plant science research.