Workshop Statistics
Download Workshop Statistics full books in PDF, epub, and Kindle. Read online free Workshop Statistics ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Author | : James H. Albert |
Publisher | : Springer Science & Business Media |
Total Pages | : 572 |
Release | : 2001-03-01 |
Genre | : Mathematics |
ISBN | : 9781930190122 |
This first edition focuses on probability and the Bayesian viewpoint. It presents basic material on probability and then introduces inference by means of Bayes' rule. The emphasis is on statistical thinking and how one learns from data. The objective is to present the basic tenets of statistical inference. Unique in its format, the text allows students to discover statistical concepts, explore statistical principles, and apply statistical techniques. In addition to the numerous activities and exercises around which the text is built, the book includes a basic text exposition for each topic, and data appendices.
Author | : Allan J. Rossman |
Publisher | : Springer Science & Business Media |
Total Pages | : 704 |
Release | : 2001-05-18 |
Genre | : Mathematics |
ISBN | : 9781930190085 |
This book focuses on probability and the Bayesian viewpoint. It presents basic material on probability and then introduces inference by means of Bayes'rule. The emphasis is on statistical thinking and how one learns from data. The objective is to present the basic tenets of statistical inference. Unique in its format, the text allows students to discover statistical concepts, explore statistical principles, and apply statistical techniques. In addition to the numerous activities and exercises around which the text is built, the book includes a basic text exposition for each topic, and data appendices.
Author | : Peter Farrell |
Publisher | : Packt Publishing Ltd |
Total Pages | : 739 |
Release | : 2020-08-18 |
Genre | : Computers |
ISBN | : 1800208367 |
With examples and activities that help you achieve real results, applying calculus and statistical methods relevant to advanced data science has never been so easy Key FeaturesDiscover how most programmers use the main Python libraries when performing statistics with PythonUse descriptive statistics and visualizations to answer business and scientific questionsSolve complicated calculus problems, such as arc length and solids of revolution using derivatives and integralsBook Description Are you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python. The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions. By the end of this book, you'll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges. What you will learnGet to grips with the fundamental mathematical functions in PythonPerform calculations on tabular datasets using pandasUnderstand the differences between polynomials, rational functions, exponential functions, and trigonometric functionsUse algebra techniques for solving systems of equationsSolve real-world problems with probabilitySolve optimization problems with derivatives and integralsWho this book is for If you are a Python programmer who wants to develop intelligent solutions that solve challenging business problems, then this book is for you. To better grasp the concepts explained in this book, you must have a thorough understanding of advanced mathematical concepts, such as Markov chains, Euler's formula, and Runge-Kutta methods as the book only explains how these techniques and concepts can be implemented in Python.
Author | : Christopher Jay Lacke |
Publisher | : John Wiley & Sons |
Total Pages | : 229 |
Release | : 2010-01-26 |
Genre | : Mathematics |
ISBN | : 0470621842 |
Workshop Statistics: Discovery Through Data has been hailed by the community for its hands-on approach to introductory statistics. This popular book has now been modified to incorporate Minitab commands and worksheets which interactively and graphically illustrate statistical concepts and facilitate the understanding of statistical processes.
Author | : Cole Nussbaumer Knaflic |
Publisher | : John Wiley & Sons |
Total Pages | : 284 |
Release | : 2015-10-09 |
Genre | : Mathematics |
ISBN | : 1119002265 |
Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Author | : Anthony So |
Publisher | : Packt Publishing Ltd |
Total Pages | : 817 |
Release | : 2020-01-29 |
Genre | : Computers |
ISBN | : 1838983082 |
Cut through the noise and get real results with a step-by-step approach to data science Key Features Ideal for the data science beginner who is getting started for the first time A data science tutorial with step-by-step exercises and activities that help build key skills Structured to let you progress at your own pace, on your own terms Use your physical print copy to redeem free access to the online interactive edition Book DescriptionYou already know you want to learn data science, and a smarter way to learn data science is to learn by doing. The Data Science Workshop focuses on building up your practical skills so that you can understand how to develop simple machine learning models in Python or even build an advanced model for detecting potential bank frauds with effective modern data science. You'll learn from real examples that lead to real results. Throughout The Data Science Workshop, you'll take an engaging step-by-step approach to understanding data science. You won't have to sit through any unnecessary theory. If you're short on time you can jump into a single exercise each day or spend an entire weekend training a model using sci-kit learn. It's your choice. Learning on your terms, you'll build up and reinforce key skills in a way that feels rewarding. Every physical print copy of The Data Science Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities, you'll always have a guided solution. You can also benchmark yourself against assessments, track progress, and receive content updates. You'll even earn a secure credential that you can share and verify online upon completion. It's a premium learning experience that's included with your printed copy. To redeem, follow the instructions located at the start of your data science book. Fast-paced and direct, The Data Science Workshop is the ideal companion for data science beginners. You'll learn about machine learning algorithms like a data scientist, learning along the way. This process means that you'll find that your new skills stick, embedded as best practice. A solid foundation for the years ahead.What you will learn Find out the key differences between supervised and unsupervised learning Manipulate and analyze data using scikit-learn and pandas libraries Learn about different algorithms such as regression, classification, and clustering Discover advanced techniques to improve model ensembling and accuracy Speed up the process of creating new features with automated feature tool Simplify machine learning using open source Python packages Who this book is forOur goal at Packt is to help you be successful, in whatever it is you choose to do. The Data Science Workshop is an ideal data science tutorial for the data science beginner who is just getting started. Pick up a Workshop today and let Packt help you develop skills that stick with you for life.
Author | : Steven L. Brunton |
Publisher | : Cambridge University Press |
Total Pages | : 615 |
Release | : 2022-05-05 |
Genre | : Computers |
ISBN | : 1009098489 |
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Author | : Geoff Cumming |
Publisher | : Routledge |
Total Pages | : 595 |
Release | : 2016-10-04 |
Genre | : Psychology |
ISBN | : 1317483375 |
This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.
Author | : Liu Peng |
Publisher | : Packt Publishing Ltd |
Total Pages | : 516 |
Release | : 2023-10-25 |
Genre | : Computers |
ISBN | : 1803237759 |
Learn the fundamentals of statistics and machine learning using R libraries for data processing, visualization, model training, and statistical inference Key Features Advance your ML career with the help of detailed explanations, intuitive illustrations, and code examples Gain practical insights into the real-world applications of statistics and machine learning Explore the technicalities of statistics and machine learning for effective data presentation Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Statistics and Machine Learning with R Workshop is a comprehensive resource packed with insights into statistics and machine learning, along with a deep dive into R libraries. The learning experience is further enhanced by practical examples and hands-on exercises that provide explanations of key concepts. Starting with the fundamentals, you’ll explore the complete model development process, covering everything from data pre-processing to model development. In addition to machine learning, you’ll also delve into R's statistical capabilities, learning to manipulate various data types and tackle complex mathematical challenges from algebra and calculus to probability and Bayesian statistics. You’ll discover linear regression techniques and more advanced statistical methodologies to hone your skills and advance your career. By the end of this book, you'll have a robust foundational understanding of statistics and machine learning. You’ll also be proficient in using R's extensive libraries for tasks such as data processing and model training and be well-equipped to leverage the full potential of R in your future projects.What you will learn Hone your skills in different probability distributions and hypothesis testing Explore the fundamentals of linear algebra and calculus Master crucial statistics and machine learning concepts in theory and practice Discover essential data processing and visualization techniques Engage in interactive data analysis using R Use R to perform statistical modeling, including Bayesian and linear regression Who this book is forThis book is for beginner to intermediate-level data scientists, undergraduate to masters-level students, and early to mid-senior data scientists or analysts looking to expand their knowledge of machine learning by exploring various R libraries. Basic knowledge of linear algebra and data modeling is a must.
Author | : Gururajan Govindan |
Publisher | : Packt Publishing Ltd |
Total Pages | : 625 |
Release | : 2020-07-29 |
Genre | : Computers |
ISBN | : 1839218126 |
Learn how to analyze data using Python models with the help of real-world use cases and guidance from industry experts Key FeaturesGet to grips with data analysis by studying use cases from different fieldsDevelop your critical thinking skills by following tried-and-true data analysisLearn how to use conclusions from data analyses to make better business decisionsBook Description Businesses today operate online and generate data almost continuously. While not all data in its raw form may seem useful, if processed and analyzed correctly, it can provide you with valuable hidden insights. The Data Analysis Workshop will help you learn how to discover these hidden patterns in your data, to analyze them, and leverage the results to help transform your business. The book begins by taking you through the use case of a bike rental shop. You'll be shown how to correlate data, plot histograms, and analyze temporal features. As you progress, you'll learn how to plot data for a hydraulic system using the Seaborn and Matplotlib libraries, and explore a variety of use cases that show you how to join and merge databases, prepare data for analysis, and handle imbalanced data. By the end of the book, you'll have learned different data analysis techniques, including hypothesis testing, correlation, and null-value imputation, and will have become a confident data analyst. What you will learnGet to grips with the fundamental concepts and conventions of data analysisUnderstand how different algorithms help you to analyze the data effectivelyDetermine the variation between groups of data using hypothesis testingVisualize your data correctly using appropriate plotting pointsUse correlation techniques to uncover the relationship between variablesFind hidden patterns in data using advanced techniques and strategiesWho this book is for The Data Analysis Workshop is for programmers who already know how to code in Python and want to use it to perform data analysis. If you are looking to gain practical experience in data science with Python, this book is for you.