Download or read book Statistics Crash Course for Beginners written by Ai Publishing and published by . This book was released on 2020-11-11 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: Frequentist and Bayesian Statistics Crash Course for Beginners Data and statistics are the core subjects of Machine Learning (ML). The reality is the average programmer may be tempted to view statistics with disinterest. But if you want to exploit the incredible power of Machine Learning, you need a thorough understanding of statistics. The reason is a Machine Learning professional develops intelligent and fast algorithms that learn from data. Frequentist and Bayesian Statistics Crash Course for Beginners presents you with an easy way of learning statistics fast. Contrary to popular belief, statistics is no longer the exclusive domain of math Ph.D.s. It's true that statistics deals with numbers and percentages. Hence, the subject can be very dry and boring. This book, however, transforms statistics into a fun subject. Frequentist and Bayesian statistics are two statistical techniques that interpret the concept of probability in different ways. Bayesian statistics was first introduced by Thomas Bayes in the 1770s. Bayesian statistics has been instrumental in the design of high-end algorithms that make accurate predictions. So even after 250 years, the interest in Bayesian statistics has not faded. In fact, it has accelerated tremendously. Frequentist Statistics is just as important as Bayesian Statistics. In the statistical universe, Frequentist Statistics is the most popular inferential technique. In fact, it's the first school of thought you come across when you enter the statistics world. How Is This Book Different? AI Publishing is completely sold on the learning by doing methodology. We have gone to great lengths to ensure you find learning statistics easy. The result: you will not get stuck along your learning journey. This is not a book full of complex mathematical concepts and difficult equations. You will find that the coverage of the theoretical aspects of statistics is proportionate to the practical aspects of the subject. The book makes the reading process easier by presenting you with three types of box-tags in different colors. They are: Requirements, Further Readings, and Hands-on Time. The final chapter presents two mini-projects to give you a better understanding of the concepts you studied in the previous eight chapters. The main feature is you get instant access to a treasure trove of all the related learning material when you buy this book. They include PDFs, Python codes, exercises, and references--on the publisher's website. You get access to all this learning material at no extra cost. You can also download the Machine Learning datasets used in this book at runtime. Alternatively, you can access them through the Resources/Datasets folder. The quick course on Python programming in the first chapter will be immensely helpful, especially if you are new to Python. Since you can access all the Python codes and datasets, a computer with the internet is sufficient to get started. The topics covered include: A Quick Introduction to Python for Statistics Starting with Probability Random Variables and Probability Distributions Descriptive Statistics: Measure of Central Tendency and Spread Exploratory Analysis: Data Visualization Statistical Inference Frequentist Inference Bayesian Inference Hands-on Projects Click the BUY NOW button and start your Statistics Learning journey.

Download or read book Statistics Crash Course for Beginners written by AI. Publishing and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Crash Course in Statistics written by Ryan J. Winter and published by SAGE Publications. This book was released on 2017-11-15 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Crash Course in Statistics by Ryan J. Winter is a short introduction to key statistical methods including descriptive statistics, one-way and two-way ANOVA, the t-test, and Chi Square. Each of the five chapters provides an overview of each method, and then walks readers through a relevant example, using SPSS to highlight how to run the statistics and how to write up the results in APA style. Each chapter ends with a self-quiz so that readers can assess their understanding of each statistical concept. This “crash course” supplement is a must-have statistics refresher for students taking research methods classes; a handy additional reference for introductory statistics students; and a guide for anyone who needs to be a consumer of statistics.

Download or read book All of Statistics written by Larry Wasserman and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.

Download or read book Statistics Crash Course for Beginners written by AI OU and published by . This book was released on 2021 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: A beginner-friendly crash course to statistics utilizing Python with an eye to preparing students for further study in machine learning Key Features A quick introduction to Python for statistics Hands-on projects for guided practice Instant access to PDFs, Python codes, exercises, and references on the publisher's website at no extra cost Book Description Data and statistics are the core subjects of Machine Learning (ML). The reality is that the average programmer may be tempted to view statistics with disinterest. But if you want to exploit the incredible power of ML, you need a thorough understanding of statistics. The reason is that a machine learning professional develops intelligent and fast algorithms that learn from data. This Statistics Crash Course for Beginners presents you with an easy way of learning statistics fast. Contrary to popular belief, statistics is no longer the exclusive domain of math PhDs. It's true that statistics deals with numbers and percentages. Hence, the subject can be very dry and boring. This book, however, transforms statistics into a fun subject. Frequentist and Bayesian statistics are two statistical techniques that interpret the concept of probability in different ways. Bayesian statistics was first introduced by Thomas Bayes in the 1770s. Bayesian statistics has been instrumental in the design of high-end algorithms that make accurate predictions. So, even after 250 years, the interest in Bayesian statistics has not faded. In fact, it has accelerated tremendously. Frequentist statistics is just as important as Bayesian statistics. In the statistical universe, Frequentist statistics is the most popular inferential technique. In fact, it's the first school of thought you come across when you enter the statistics world. By the end of this course, you will have built a solid foundation in statistical theory and practice that will prepare you for further study in machine learning and a career in programming. The code bundle for this course is available at https://www.aispublishing.net/nlp-crash-course1605125706681 What you will learn Get a crash course in Python for statistics Utilize Python to determine probability, random variables, and probability distributions Study descriptive statistics, measuring central tendency and spread Perform exploratory analysis, such as data visualization Practice statistical inference, frequentist inference, and Bayesian inference Successfully complete several real-world projec...

Download or read book Essential Statistics for Data Science A Concise Crash Course written by Mu Zhu and published by Oxford University Press. This book was released on 2023-04-04 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essential Statistics for Data Science: A Concise Crash Course is for students entering a serious graduate program or advanced undergraduate teaching in data science without knowing enough statistics. The three part text introduces readers to the basics of probability and random variables and guides them towards relatively advanced topics in both frequentist and Bayesian in a matter of weeks. Part I, Talking Probability explains the statistical approach to analysing data with a probability model to describe the data generating process. Part II, Doing Statistics demonstrates how the unknown quantities in data i.e. it's parameters is applicable in statistical interference. Part III, Facing Uncertainty explains the importance of explicity describing how much uncertainty is caused by parameters with intrinsic scientific meaning and how to take that into account when making decisions. Essential Statistics for Data Science: A Concise Crash Course provides an in-depth introduction for beginners, while being more focused than a typical undergraduate text, but still lighter and more accessible than an average graduate text.

Download or read book Data Science Crash Course for Beginners with Python Fundamentals and Practices with Python written by Ai Publishing and published by AI Publishing LLC. This book was released on 2020-08-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Crash Course for Beginners with Python Data Science is here to stay. The tremendous growth in the volume, velocity, and variety of data has a substantial impact on every aspect of a business. While data continues to grow exponentially, accuracy remains a problem. This is where data scientists play a decisive role. A data scientist analyzes data, discovers new insights, paints a picture, and creates a vision. And a competent data scientist will provide a business with the competitive edge it needs and address pressing business problems. Data Science Crash Course for Beginners with Python presents you with a hands-on approach to learn data science fast. How Is This Book Different? Every book by AI Publishing has been carefully crafted. This book lays equal emphasis on the theoretical sections as well as the practical aspects of data science. Each chapter provides the theoretical background behind the numerous data science techniques, and practical examples explain the working of these techniques. In the Further Reading section of each chapter, you will find the links to informative data science posts. This book presents you with the tools and packages you need to kick-start data science projects to resolve problems of practical nature. Special emphasis is laid on the main stages of a data science pipeline--data acquisition, data preparation, exploratory data analysis, data modeling and evaluation, and interpretation of the results. In the Data Science Resources section, links to data science resources, articles, interviews, and data science newsletters are provided. The author has also put together a list of contests and competitions that you can try on your own. Another added benefit of buying this book is you get instant access to all the learning material presented with this book-- PDFs, Python codes, exercises, and references--on the publisher's website. They will not cost you an extra cent. The datasets used in this book can be downloaded at runtime, or accessed via the Resources/Datasets folder. The author simplifies your learning by holding your hand through everything. The step by step description of the installation of the software you need for implementing the various data science techniques in this book is guaranteed to make your learning easier. So, right from the beginning, you can experiment with the practical aspects of data science. You'll also find the quick course on Python programming in the second and third chapters immensely helpful, especially if you are new to Python. This book gives you access to all the codes and datasets. So, access to a computer with the internet is sufficient to get started. The topics covered include: Introduction to Data Science and Decision Making Python Installation and Libraries for Data Science Review of Python for Data Science Data Acquisition Data Preparation (Preprocessing) Exploratory Data Analysis Data Modeling and Evaluation Using Machine Learning Interpretation and Reporting of Findings Data Science Projects Key Insights and Further Avenues Click the BUY button to start your Data Science journey.

Download or read book Statistics Crash Course for Beginners written by OU. AI Sciences OU and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Beyond Basic Statistics written by Kristin H. Jarman and published by John Wiley & Sons. This book was released on 2015-04-22 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statistics—the art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques. Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering life’s important questions. Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features: Plentiful examples throughout aimed to strengthen readers’ understanding of the statistical concepts and methods A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression A case study in each chapter that illustrates the use of the presented techniques Highlights of well-known shortcomings that can lead to false conclusions An introduction to advanced techniques such as validation and bootstrapping Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.

Download or read book Essentials of Data Science written by Max Anderson and published by . This book was released on 2019-10-04 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: This mini course provides a super basic looking to data scienceThis mini course is designed to help those of you who are curious about data science develop a better and more specific understanding of the topic.In this crash course for beginners, you will learn about: Statistics: we talk about the types of data you'll encounter, types of averages, variance, standard deviation, correlation, and more.Data visualization: we talk about why we need to visualize our data, and the different ways of doing it (1 variable graphs, 2 variable graphs and 3 variable graphs.) Programming: we talk about why programming helps us with data science including the ease of automation and recommended Python libraries for you to get started with data science.This mini-course gives you a good basic insight into what the term 'data science' exactly entails, and it will triggers your curiosity to look into a career in data science!Scroll back up to the top of this page and hit BUY IT NOW to get your copy and start learning all you need to know about data science.

Download or read book Python Crash Course for Data Analysis A Complete Beginner Guide for Python Coding NumPy Pandas and Data Visualization written by Ai Publishing and published by AI Publishing LLC. This book was released on 2019-09-22 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: **GET YOUR COPY NOW, the price will be 21.99$ soon**Learn Python coding for Data Analysis from scratch very easilyWelcome to the Python Crash Course for Data Analysis!The book offers you a solid introduction to the world of Python Coding for data analysis. In this book, you'll learn fundamentals that will enable you to go further in Python Coding, launch or advance a career, and join the next generation of Data Analyst talent that will help define a beneficial, new, powered future for our world. You will study important libraries such as NumPy, Pandas and some Data Visualization libraries.Educational Objectives: This introductory book teaches the foundational skills all Python programmers use to analyze data. It is ideal for beginners who want to learn Python coding or Python for Data Analysis, make informed choices about career goals, and set themselves up for success in this path. At the end of this learning, you will become an great Python Programmer for data Analysis, and learn to analyse data using frameworks like NumPy, Pandas and Matplotlib. Prerequisites: No prior experience with programming is required. You will need to be comfortable with basic computer skills, such as managing files, running programs, and using a web browser to navigate the Internet.You will need to be self-driven and genuinely interested in the Python Coding. No matter how well structured the program is, any attempt to learn programming will involve many hours of studying, practice, and experimentation. Success in this book requires devoting at least 10 hours to your work. This requires some tenacity, and it is especially difficult to do if you don't find Python coding interesting or aren't willing to play around and tinker with your code-so drive, curiosity, and an adventurous attitude are highly recommended!You will need to be able to learn English.Contact Info: While going through the book, if you have questions about anything, you can reach us at [email protected].**GET YOUR COPY NOW, the price will be 15.99$ soon**

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

Download or read book The Book of R written by Tilman M. Davies and published by No Starch Press. This book was released on 2016-07-16 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Download or read book C Crash Course written by Josh Lospinoso and published by No Starch Press. This book was released on 2019-09-24 with total page 793 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fast-paced, thorough introduction to modern C++ written for experienced programmers. After reading C++ Crash Course, you'll be proficient in the core language concepts, the C++ Standard Library, and the Boost Libraries. C++ is one of the most widely used languages for real-world software. In the hands of a knowledgeable programmer, C++ can produce small, efficient, and readable code that any programmer would be proud of. Designed for intermediate to advanced programmers, C++ Crash Course cuts through the weeds to get you straight to the core of C++17, the most modern revision of the ISO standard. Part 1 covers the core of the C++ language, where you'll learn about everything from types and functions, to the object life cycle and expressions. Part 2 introduces you to the C++ Standard Library and Boost Libraries, where you'll learn about all of the high-quality, fully-featured facilities available to you. You'll cover special utility classes, data structures, and algorithms, and learn how to manipulate file systems and build high-performance programs that communicate over networks. You'll learn all the major features of modern C++, including: Fundamental types, reference types, and user-defined types The object lifecycle including storage duration, memory management, exceptions, call stacks, and the RAII paradigm Compile-time polymorphism with templates and run-time polymorphism with virtual classes Advanced expressions, statements, and functions Smart pointers, data structures, dates and times, numerics, and probability/statistics facilities Containers, iterators, strings, and algorithms Streams and files, concurrency, networking, and application development With well over 500 code samples and nearly 100 exercises, C++ Crash Course is sure to help you build a strong C++ foundation.

Download or read book AP Statistics Crash Course For the 2020 Exam Book Online written by Michael D'Alessio and published by Research & Education Assoc.. This book was released on 2020-02-14 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: For the 2020 Exam! AP® Statistics Crash Course® A Higher Score in Less Time! Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. Are you crunched for time? Have you started studying for your Advanced Placement® Statistics exam yet? How will you memorize everything you need to know before the test? Do you wish there was a fast and easy way to study for the exam AND boost your score? If this sounds like you, don't panic. REA's Crash Course for AP® Statistics is just what you need. Our Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know The Crash Course is based on an in-depth analysis of the AP® Statistics course description outline and actual AP® test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Written by an experienced AP® Statistics teacher, our easy-to-read format gives you a crash course in exploring data, planning a study, anticipating patterns, and statistical inferences. Expert Test-taking Strategies Our AP® author shares detailed question-level strategies and explains the best way to answer the questions you’ll find on the AP® exam. By following his expert advice, you can boost your overall point score! Practice questions – a mini-test in the book, a full-length exam online. Are you ready for your exam? Try our focused practice set inside the book. Then go online to take our full-length practice exam. You’ll get the benefits of timed testing, detailed answers, and automatic scoring that pinpoints your performance based on the official AP® exam topics – so you'll be confident on test day. Whether you’re cramming for the exam or looking to recap and reinforce your teacher’s lessons, Crash Course® is the study guide every AP® student needs. About the Author Michael D’Alessio earned his B.S. in Biology from Seton Hall University and his M.S. in Biomedical Sciences from the University of Medicine and Dentistry of New Jersey. In 2004, he earned his Executive Masters of Arts in Educational Leadership from Seton Hall University. Mr. D’Alessio has had an extensive career teaching all levels of mathematics and science, including AP® statistics, chemistry, biology, physics, algebra, calculus and geometry. In 2003, Mr. D’Alessio received the Governor’s Teacher of the Year recognition for Watchung Hills Regional High School. In 2004, Mr. D’Alessio received a Certificate of Recognition of Excellence in Science Teaching from Sigma Xi, the Scientific Research Society of Rutgers University and in 2005, he was voted National Honor Society Teacher of the Year by the students of Watchung Hills. Currently, Mr. D’Alessio serves as the Supervisor of the Mathematics and Business Department at Watchung Hills Regional High School in Warren, New Jersey, overseeing 30 teachers.

Download or read book Statistics Crash Course written by IntroBooks and published by IntroBooks. This book was released on 2018-02-22 with total page 37 pages. Available in PDF, EPUB and Kindle. Book excerpt: A crash course in statistics delves into key statistical methods, namely Chi Square, t-test, ANOVA and descriptive statistics. It equally gives an overview of statistical methods as well as various discussions of the statistical tests relating to various database culled from various sources, like the survey of student spending on textbooks, etc. Also, detailed demonstration of various data analysis in SPSS was considered via statistical test. Descriptive statistics, being an outstanding aspect of this broad field, was considered in detail, as well as the field of nonparametric statistics. Furthermore, this text will look into the One-Way and the Two-Way statistics. Parametric and nonparametric statistics is a very important aspect of the subject matter, thereby necessitating their mention in this text. Mention will be made of their theories and practical aspect towards enlightening the reader about how each of them is applied in real-life situations. Also, the reader will get enlightened on how each of these statistical methods differs.

Download or read book Data Science from Scratch written by Joel Grus and published by "O'Reilly Media, Inc.". This book was released on 2015-04-14 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases