Functions, Data and Models PDF Download

Author: Sheldon P. Gordon
Publisher: MAA
ISBN: 0883857677
Category : Mathematics
Languages : en
Pages : 511

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Book Description
Focuses primarily on mathematical concepts and mathematical thinking, thereby achieving a balance among geometric, numerical, symbolic, and statistical approaches, rather than focusing on algebraic manipulation. Gordon incorporates a significant amount of statistical reasoning and methods as natural applications of more standard college algebra topics. --From publisher description.

Author: Cram101 Textbook Reviews
Publisher: Cram101
ISBN: 9781497018495
Category :
Languages : en
Pages : 76

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Book Description
Never HIGHLIGHT a Book Again! Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780883857670. This item is printed on demand.

Author: Mary Ellen Davis
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 410

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Book Description
This book helps readers develop the quantitative literacy skills and savvy needed to function effectively in society and the workplace. It focuses on "mathematical modeling" and the use of elementary mathematics--e.g., numbers and measurement, algebra, geometry, and data exploration--to investigate real-world problems and questions. It assumes no technology other than the use of graphing calculators, and provides a comprehensive technology support system on an accompanying CD-ROM and web site. Linear Functions and Models. Quadratic Functions and Models. Natural Growth Models. Exponential and Trigonometric Models. Polynomial Models and Linear Systems. Optimization Problems. Bounded Growth Models. For anyone wanting to develop proficiency in mathematical modeling.

Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521

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Book Description
Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Author:
Publisher:
ISBN: 0198824726
Category :
Languages : en
Pages : 812

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Book Description

Author: James Ramsay
Publisher: Springer Science & Business Media
ISBN: 0387981853
Category : Computers
Languages : en
Pages : 213

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Book Description
The book provides an application-oriented overview of functional analysis, with extended and accessible presentations of key concepts such as spline basis functions, data smoothing, curve registration, functional linear models and dynamic systems Functional data analysis is put to work in a wide a range of applications, so that new problems are likely to find close analogues in this book The code in R and Matlab in the book has been designed to permit easy modification to adapt to new data structures and research problems

Author: Peter X. -K. Song
Publisher: Springer Science & Business Media
ISBN: 038771393X
Category : Mathematics
Languages : en
Pages : 352

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Book Description
This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

Author: Katherine Franklin
Publisher: Brooks/Cole
ISBN: 9780534132842
Category : Mathematics
Languages : en
Pages : 714

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Book Description
While maintaining its focus on functions and graphs this book gives the adequately prepared algebra student the right start and flexible goals.

Author: Scott Wlaschin
Publisher: Pragmatic Bookshelf
ISBN: 1680505491
Category : Computers
Languages : en
Pages : 426

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Book Description
You want increased customer satisfaction, faster development cycles, and less wasted work. Domain-driven design (DDD) combined with functional programming is the innovative combo that will get you there. In this pragmatic, down-to-earth guide, you'll see how applying the core principles of functional programming can result in software designs that model real-world requirements both elegantly and concisely - often more so than an object-oriented approach. Practical examples in the open-source F# functional language, and examples from familiar business domains, show you how to apply these techniques to build software that is business-focused, flexible, and high quality. Domain-driven design is a well-established approach to designing software that ensures that domain experts and developers work together effectively to create high-quality software. This book is the first to combine DDD with techniques from statically typed functional programming. This book is perfect for newcomers to DDD or functional programming - all the techniques you need will be introduced and explained. Model a complex domain accurately using the F# type system, creating compilable code that is also readable documentation---ensuring that the code and design never get out of sync. Encode business rules in the design so that you have "compile-time unit tests," and eliminate many potential bugs by making illegal states unrepresentable. Assemble a series of small, testable functions into a complete use case, and compose these individual scenarios into a large-scale design. Discover why the combination of functional programming and DDD leads naturally to service-oriented and hexagonal architectures. Finally, create a functional domain model that works with traditional databases, NoSQL, and event stores, and safely expose your domain via a website or API. Solve real problems by focusing on real-world requirements for your software. What You Need: The code in this book is designed to be run interactively on Windows, Mac and Linux.You will need a recent version of F# (4.0 or greater), and the appropriate .NET runtime for your platform.Full installation instructions for all platforms at fsharp.org.

Author: Katherine Yoshiwara
Publisher: Thomson Brooks/Cole
ISBN: 9780495190141
Category : Algebra
Languages : en
Pages :

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Book Description
The Fourth Edition of Yoshiwara and Yoshiwara's MODELING, FUNCTIONS, AND GRAPHS: ALGEBRA FOR COLLEGE STUDENTS includes content found in a typical algebra course, along with introductions to curve-fitting and display of data. Yoshiwara and Yoshiwara focus on three core themes throughout their textbook: Modeling, Functions, and Graphs. In their work of modeling and functions, the authors utilize the Rule of Four, which is that all problems should be considered using algebraic, numerical, graphical, and verbal methods. The authors motivate students to acquire the skills and techniques of algebra by placing them in the context of simple applications that use real-life data.