Think Stats


Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491907371
Category: Computers
Page: 226
View: 5798

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If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you’ll learn the entire process of exploratory data analysis—from collecting data and generating statistics to identifying patterns and testing hypotheses. You’ll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that’s cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data

Think Stats


Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1449313108
Category: Computers
Page: 138
View: 8558

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If you know how to program, you have the skills to turn data into knowledge using the tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts. Develop your understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Learn topics not usually covered in an introductory course, such as Bayesian estimation Import data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data

Think Stats


Author: Allen Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1449307116
Category: Computers
Page: 119
View: 1996

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Shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python -- Back cover.

Think Bayes


Author: Allen Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491945443
Category: Computers
Page: 210
View: 7106

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If you know how to program with Python and also know a little about probability, you’re ready to tackle Bayesian statistics. With this book, you'll learn how to solve statistical problems with Python code instead of mathematical notation, and use discrete probability distributions instead of continuous mathematics. Once you get the math out of the way, the Bayesian fundamentals will become clearer, and you’ll begin to apply these techniques to real-world problems. Bayesian statistical methods are becoming more common and more important, but not many resources are available to help beginners. Based on undergraduate classes taught by author Allen Downey, this book’s computational approach helps you get a solid start. Use your existing programming skills to learn and understand Bayesian statistics Work with problems involving estimation, prediction, decision analysis, evidence, and hypothesis testing Get started with simple examples, using coins, M&Ms, Dungeons & Dragons dice, paintball, and hockey Learn computational methods for solving real-world problems, such as interpreting SAT scores, simulating kidney tumors, and modeling the human microbiome.

Think Python

How to Think Like a Computer Scientist
Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491939419
Category: Computers
Page: 292
View: 7334

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If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, you’ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand objects, methods, and object-oriented programming Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design, data structures, and GUI-based programs through case studies

Think Complexity

Complexity Science and Computational Modeling
Author: Allen Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1492040150
Category: Computers
Page: 200
View: 2324

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Complexity science uses computation to explore the physical and social sciences. In Think Complexity, you’ll use graphs, cellular automata, and agent-based models to study topics in physics, biology, and economics. Whether you’re an intermediate-level Python programmer or a student of computational modeling, you’ll delve into examples of complex systems through a series of worked examples, exercises, case studies, and easy-to-understand explanations. In this updated second edition, you will: Work with NumPy arrays and SciPy methods, including basic signal processing and Fast Fourier Transform Study abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines Get Jupyter notebooks filled with starter code and solutions to help you re-implement and extend original experiments in complexity; and models of computation like Turmites, Turing machines, and cellular automata Explore the philosophy of science, including the nature of scientific laws, theory choice, and realism and instrumentalism Ideal as a text for a course on computational modeling in Python, Think Complexity also helps self-learners gain valuable experience with topics and ideas they might not encounter otherwise.

Think Perl 6

How to Think Like a Computer Scientist
Author: Laurent Rosenfeld,Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491980508
Category: Computers
Page: 466
View: 3342

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Want to learn how to program and think like a computer scientist? This practical guide gets you started on your programming journey with the help of Perl 6, the younger sister of the popular Perl programming language. Ideal for beginners, this hands-on book includes over 100 exercises with multiple solutions, and more than 1,000 code examples so you can quickly practice what you learn. Experienced programmers—especially those who know Perl 5—will also benefit. Divided into two parts, Think Perl 6 starts with basic concepts that every programmer needs to know, and then focuses on different programming paradigms and some more advanced programming techniques. With two semesters’ worth of lessons, this book is the perfect teaching tool for computer science beginners in colleges and universities. Learn basic concepts including variables, expressions, statements, functions, conditionals, recursion, and loops Understand commonly used basic data structures and the most useful algorithms Dive into object-oriented programming, and learn how to construct your own types and methods to extend the language Use grammars and regular expressions to analyze textual content Explore how functional programming can help you make your code simpler and more expressive

Think DSP

Digital Signal Processing in Python
Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 149193851X
Category: Technology & Engineering
Page: 168
View: 6263

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If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.

Statistics for People Who (Think They) Hate Statistics


Author: Neil J. Salkind
Publisher: SAGE Publications
ISBN: 1506333850
Category: Social Science
Page: 480
View: 2520

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The Sixth Edition of Neil J. Salkind’s best-selling Statistics for People Who (Think They) Hate Statistics promises to ease student anxiety around an often intimidating subject with a humorous, personable, and informative approach. Salkind guides students through various statistical procedures, beginning with descriptive statistics, correlation, and graphical representation of data, and ending with inferential techniques and analysis of variance. New to this edition is an introduction to working with large data sets.

Data Analysis with Open Source Tools

A Hands-On Guide for Programmers and Data Scientists
Author: Philipp K. Janert
Publisher: "O'Reilly Media, Inc."
ISBN: 1449396658
Category: Computers
Page: 540
View: 9669

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Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with concepts through hands-on workshops at the end of each chapter. Above all, you'll learn how to think about the results you want to achieve -- rather than rely on tools to think for you. Use graphics to describe data with one, two, or dozens of variables Develop conceptual models using back-of-the-envelope calculations, as well asscaling and probability arguments Mine data with computationally intensive methods such as simulation and clustering Make your conclusions understandable through reports, dashboards, and other metrics programs Understand financial calculations, including the time-value of money Use dimensionality reduction techniques or predictive analytics to conquer challenging data analysis situations Become familiar with different open source programming environments for data analysis "Finally, a concise reference for understanding how to conquer piles of data."--Austin King, Senior Web Developer, Mozilla "An indispensable text for aspiring data scientists."--Michael E. Driscoll, CEO/Founder, Dataspora

Think Java

How to Think Like a Computer Scientist
Author: Allen B. Downey,Chris Mayfield
Publisher: "O'Reilly Media, Inc."
ISBN: 1491929537
Category: Computers
Page: 252
View: 1774

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Currently used at many colleges, universities, and high schools, this hands-on introduction to computer science is ideal for people with little or no programming experience. The goal of this concise book is not just to teach you Java, but to help you think like a computer scientist. You’ll learn how to program—a useful skill by itself—but you’ll also discover how to use programming as a means to an end. Authors Allen Downey and Chris Mayfield start with the most basic concepts and gradually move into topics that are more complex, such as recursion and object-oriented programming. Each brief chapter covers the material for one week of a college course and includes exercises to help you practice what you’ve learned. Learn one concept at a time: tackle complex topics in a series of small steps with examples Understand how to formulate problems, think creatively about solutions, and write programs clearly and accurately Determine which development techniques work best for you, and practice the important skill of debugging Learn relationships among input and output, decisions and loops, classes and methods, strings and arrays Work on exercises involving word games, graphics, puzzles, and playing cards

Statistical Rethinking

A Bayesian Course with Examples in R and Stan
Author: Richard McElreath
Publisher: CRC Press
ISBN: 1315362619
Category: Mathematics
Page: 487
View: 545

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Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Think Data Structures

Algorithms and Information Retrieval in Java
Author: Allen B Downey
Publisher: "O'Reilly Media, Inc."
ISBN: 1491972343
Category:
Page: N.A
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If you're a student studying computer science or a software developer preparing for technical interviews, this practical book will help you learn and review some of the most important ideas in software engineering--data structures and algorithms--in a way that's clearer, more concise, and more engaging than other materials. By emphasizing practical knowledge and skills over theory, author Allen Downey shows you how to use data structures to implement efficient algorithms, and then analyze and measure their performance. You'll explore the important classes in the Java collections framework (JCF), how they're implemented, and how they're expected to perform. Each chapter presents hands-on exercises supported by test code online. Use data structures such as lists and maps, and understand how they work Build an application that reads Wikipedia pages, parses the contents, and navigates the resulting data tree Analyze code to predict how fast it will run and how much memory it will require Write classes that implement the Map interface, using a hash table and binary search tree Build a simple web search engine with a crawler, an indexer that stores web page contents, and a retriever that returns user query results Other books by Allen Downey include Think Java, Think Python, Think Stats, and Think Bayes.

Practical Statistics for Data Scientists

50 Essential Concepts
Author: Peter Bruce,Andrew Bruce
Publisher: "O'Reilly Media, Inc."
ISBN: 1491952911
Category: Computers
Page: 318
View: 2649

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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

Chances Are

The Only Statistic Book You'll Ever Need
Author: Steve Slavin
Publisher: Madison Books
ISBN: 146162293X
Category: Mathematics
Page: 224
View: 9464

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Chances Are is the first book to make statistics accessible to everyone, regardless of how much math you remember from school.

An Introduction to Statistics with Python

With Applications in the Life Sciences
Author: Thomas Haslwanter
Publisher: Springer
ISBN: 3319283162
Category: Computers
Page: 278
View: 5235

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This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis.

Think and Grow Rich


Author: Napoleon Hill,Wyatt North
Publisher: Wyatt North Publishing, LLC
ISBN: N.A
Category: Business & Economics
Page: 300
View: 5299

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Think and Grow Rich is a motivational personal development and self-help book by Napoleon Hill. The book was heavily inspired by the work of Andrew Carnegie. While the title focuses on how to get rich, the author explains that the philosophy taught in the book can be used to help people succeed in all lines of work and to do or be almost anything they want.

OpenIntro Statistics


Author: David Diez,Christopher Barr,Mine Çetinkaya-Rundel
Publisher: N.A
ISBN: 9781943450046
Category:
Page: N.A
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The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.

Trump: The Art of the Deal


Author: Donald J. Trump,Tony Schwartz
Publisher: Ballantine Books
ISBN: 9780307575333
Category: Business & Economics
Page: 384
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President Donald J. Trump lays out his professional and personal worldview in this classic work—a firsthand account of the rise of America’s foremost deal-maker. “I like thinking big. I always have. To me it’s very simple: If you’re going to be thinking anyway, you might as well think big.”—Donald J. Trump Here is Trump in action—how he runs his organization and how he runs his life—as he meets the people he needs to meet, chats with family and friends, clashes with enemies, and challenges conventional thinking. But even a maverick plays by rules, and Trump has formulated time-tested guidelines for success. He isolates the common elements in his greatest accomplishments; he shatters myths; he names names, spells out the zeros, and fully reveals the deal-maker’s art. And throughout, Trump talks—really talks—about how he does it. Trump: The Art of the Deal is an unguarded look at the mind of a brilliant entrepreneur—the ultimate read for anyone interested in the man behind the spotlight. Praise for Trump: The Art of the Deal “Trump makes one believe for a moment in the American dream again.”—The New York Times “Donald Trump is a deal maker. He is a deal maker the way lions are carnivores and water is wet.”—Chicago Tribune “Fascinating . . . wholly absorbing . . . conveys Trump’s larger-than-life demeanor so vibrantly that the reader’s attention is instantly and fully claimed.”—Boston Herald “A chatty, generous, chutzpa-filled autobiography.”—New York Post

The World Factbook


Author: Central Intelligence Agency
Publisher: Masterlab
ISBN: 8379912136
Category: Reference
Page: 3100
View: 7543

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The World Factbook provides information on the history, people, government, economy, geography, communications, transportation, military, and transnational issues for 267 world entities. The World Factbook is prepared by the Central Intelligence Agency. Comprehensive guide full of facts, maps, flags, and detailed information. A must for travellers, businessmen, politicians, and all who wants to know more about our fascinating world. -- We share these facts with the people of all nations in the belief that knowledge of the truth underpins the functioning of free societies (From official webpage). Tags: world, guide, facts, almanach