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pstrongEmbrace object-oriented programming and explore language complexities, design patterns, and smart programming techniques using this hands-on guide with C 20 compliant examplesstrongppbrppstrongKey Features strongpulliApply object-oriented design concepts in C using direct language features and refined programming techniquesliliDiscover sophisticated programming solutions with nuances to become an efficient programmerliliExplore design patterns as proven solutions for writing scalable and maintainable C softwareliulpbrppstrongBook Description strongppEven though object-oriented software design enables more easily maintainable code, companies choose C as an OO language for its speed. Object-oriented programming in C is not automatic - it is crucial to understand OO concepts and how they map to both C language features and OOP techniques. Distinguishing your code by utilizing well-tested, creative solutions, which can be found in popular design patterns, is crucial in today's marke

Deciphering Object | Oriented Programming with C++ | Kirk Dorothy R. | Twarda

pstrongDoing Meta-Analysis with R A Hands-On Guidestrong serves as an accessible introduction on how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered, including calculation and pooling of outcome measures, forest plots, heterogeneity diagnostics, subgroup analyses, meta-regression, methods to control for publication bias, risk of bias assessments and plotting tools. Advanced but highly relevant topics such as network meta-analysis, multi-three-level meta-analyses, Bayesian meta-analysis approaches and SEM meta-analysis are also covered. A companion R package, idmetari, is introduced at the beginning of the guide. It contains data sets and several helper functions for the imetai and imetafori package used in the guide. ppThe programming and statistical background covered in the book are kept at a non-expert level, making the book widely accessible. ppbFeaturesbbr- Contains two introductory chapters on how to set up an R environment and do basic importsm

Doing Meta | Analysis with R | Harrer Mathias | Twarda

pThis textbook is a comprehensive guide to machine learning and artificial intelligence tailored for students in business and economics. It takes a hands-on approach to teach machine learning, emphasizing practical applications over complex mathematical concepts. Students are not required to have advanced mathematics knowledge such as matrix algebra or calculus.ppThe author introduces machine learning algorithms, utilizing the widely used R language for statistical analysis. Each chapter includes examples, case studies, and interactive tutorials to enhance understanding. No prior programming knowledge is needed. The book leverages the tidymodels package, an extension of R, to streamline data processing and model workflows. This package simplifies commands, making the logic of algorithms more accessible by minimizing programming syntax hurdles. The use of tidymodels ensures a unified experience across various machine learning models.ppWith interactive tutorials that students can downloa

Practical Machine Learning with R | Lange Carsten | Twarda

pThis book provides hands-on guidance for researchers and practitioners in criminal justice and criminology to perform statistical analyses and data visualization in the free and open-source software R. It offers a step-by-step guide for beginners to become familiar with the RStudio platform and tidyverse set of packages. p This volume will help users master the fundamentals of the R programming language, providing tutorials in each chapter that lay out research questions and hypotheses centering around a real criminal justice dataset, such as data from the National Survey on Drug Use and Health, National Crime Victimization Survey, Youth Risk Behavior Surveillance System, The Monitoring the Future Study, and The National Youth Survey. Users will also learn how to manipulate common sources of agency data, such as calls-for-service CFS data. The end of each chapter includes exercises that reinforce the R tutorial examples, designed to help master the software as well as to provide pract

A Beginner's Guide to Statistics for Criminology and Criminal Justice Using R | Wooditch Alese | Paperback | Twarda

pData analytics may seem daunting, but if you're an experienced Excel user, you have a unique head start. With this hands-on guide, intermediate Excel users will gain a solid understanding of analytics and the data stack. By the time you complete this book, you'll be able to conduct exploratory data analysis and hypothesis testing using a programming language. p Exploring and testing relationships are core to analytics. By using the tools and frameworks in this book, you'll be well positioned to continue learning more advanced data analysis techniques. Author George Mount, founder and CEO of Stringfest Analytics, demonstrates key statistical concepts with spreadsheets, then pivots your existing knowledge about data manipulation into R and Python programming. p This practical book guides you through ul libFoundations of analytics in Excel b Use Excel to test relationships between variables and build compelling demonstrations of important concepts in statistics and analytics libFrom Exce

Advancing Into Analytics | Mount George | Twarda

pbLearn data science by doing data science bb bp pbiData Science Using Python and R ibbwill get you plugged into the world's two most widespread open-source platforms for data science Python and R.bp pData science is hot. iBloomberg icalled data scientist the hottest job in America. Python and R are the top two open-source data science tools in the world. In iData Science Using Python and Ri, you will learn step-by-step how to produce hands-on solutions to real-world business problems, using state-of-the-art techniques. p piData Science Using Python and Ri is written for the general reader with no previous analytics or programming experience. An entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R.p pThose with analytics experience will appreciate having a one-stop shop for learning how to do data science using Python and R. Topics covered include d

Data Science Using Python and R | Larose Daniel T. | Twarda | Twarda

Gain the hands-on experience and knowledge to solve real financial problems while taking your Excel spreadsheet skills to a new level with Mayes' FINANCIAL ANALYSIS WITH MICROSOFT EXCEL, 9E. This edition provides a reader-friendly solid foundation in corporate finance while teaching you to maximize the spreadsheet tools that professionals use every day. Packed with interesting examples, this edition covers today's most important corporate finance topics and tools, including financial statements, budgets, the Security Market Security Line, pro forma financial statements, cost of capital, Visual Basic Applications VBA programming and Excel pivot tables. You study the latest information on time series forecasting and work with Excel's Get  Transform feature to process large data files. This edition's self-directed learning approach and numerous self-study tools let you strengthen spreadsheet skills while equipping you with the expertise today's employers want in corporate finance.

Financial Analysis with Microsoft Excel | Mayes Timothy R. | Paperback | Twarda

pThis concise and accessible textbook will enable readers to quickly develop the working skills necessary to solve computational problems in a server-based environment, using HTML and PHP. The importance of learning by example as opposed to simply learning by copying is emphasized through extensive use of hands-on exercises and examples, with a specific focus on useful science and engineering applications. The clearly-written text is designed to be simple to follow for the novice student, without requiring any background in programming or mathematics beyond algebra.pTopics and features describes the creation of HTML pages and the characteristics of HTML documents, showing how to use HTML tables, forms, lists, and frames to organize documents for use with PHP applications explains how to set up a PHP environment, using a local or remote server introduces the capabilities and syntax of the PHP language, including coverage of array syntax and use examines user-defined functions in program

Programming in HTML and PHP | Brooks David R. | Twarda

This is the third, newly revised and extended edition of this successful book that has already been translated into three languages. Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on with thousands of lines of heavily annotated code for all computations and plots. However, this edition has been updated based on many workshopsbootcamps taught by the author all over the world for the past few years This edition has been didactically streamlined with regard to its exposition, it adds two new chapters - one on mixed-effects modeling, one on classification and regression trees as well as random forests - plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelationruns, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials.

Statistics for Linguistics with R | Gries Stefan Th | Twarda

In this practical, project-based book, music students, educators, and coders receive the necessary tools to engage with real-world experiences in computation and creativity using the programming language Scratch. Designed to teach students the fundamental concepts of computational thinking through interactive music, sound, and media, projects vary in complexity and encourage readers to make music through playing and creating music. pThis book introduces readers to concepts in computational thinking and coding alongside parallel concepts in music, creative sound, and interaction. The book begins with a gentle introduction to the Scratch 3.0 programming environment through hands-on projects using a computer keyboard and mouse to make music and control sounds, creating original sounds, and performing them as an instrument. The next chapters introduce programming musical sequences, melodies, and structures, and assembling them into a virtual band that can be performed live or automated thr

Scratch Music Projects | Brown Andrew R. | Paperback | Twarda

pppThis undergraduate textbook presents an inquiry-based learning course in stochastic models and computing designed to serve as a first course in probability. Its modular structure complements a traditional lecture format, introducing new topics chapter by chapter with accompanying projects for group collaboration. The text addresses probability axioms leading to Bayes' theorem, discrete and continuous random variables, Markov chains, and Brownian motion, as well as applications including randomized algorithms, randomized surveys, Benford's law, and Monte Carlo methods. pAdopting a unique application-driven approach to better study probability in action, the book emphasizes data, simulation, and games to strengthen reader insight and intuition while proving theorems. Additionally, the text incorporates codes and exercises in the Julia programming language to further promote a hands-on focus in modelling. Students should have prior knowledge of single variable calculus.pppGiray  kten r

Probability and Simulation | kten Giray | Paperback | Twarda

pbGuides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming languagebp pMachine learning--a branch of Artificial Intelligence AI which enables computers to improve their results and learn new approaches without explicit instructions--allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. iPractical Machine Learning in Ri provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. p pBestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, demonstrate its organizational benefits, and provide hands-on examples created in the R programming language. A perfect guide for professional self-taught learners or students in an introductory machine learning course, this reader-friendly book illustrates the numerous real-world business uses o

Practical Machine Learning in R | Nwanganga Fred | Paperback | Twarda

pLearn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.ppThe second half of iLearning Ri shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code.pulliWrite a simple R program, and discover what the language can doliliUse data types such as vectors, arrays, lists, data frames, and stringsliliExecute code conditionally or repeatedly with branches and loopsliliApply R add-on packages, and package your own work for othersliliLearn how to clean data you import from a variety of sourcesliliUnderstand data through visualization and summary statisticsliliUse statist

Learning R | Cotton Richard | Twarda

piThe Book of Ri 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.ppYou'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.ppDozens of hands-on exercises with downloadable solutions take you from theory to practice, as you learn pulliThe fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loo

The Book of R | Davies Tilman M. | Twarda

pemFrom Data to Decisions in Music Education Researchem provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data, this book draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems.ppAll of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers pul p p liA clear and comprehensive framework for thinking about data analysis processes in a music education context.li p p liAn overview of common data structures and data types used in statistical programming and data analytics. li p

From Data to Decisions in Music Education Research | Wesolowski Brian C. | Twarda

pbA hands-on lab guide in the R programming language that enables students in the life sciences to reason quantitatively about living systems across scalesb pThis lab guide accompanies the textbook iQuantitative Biosciencesi, providing students with the skills they need to translate biological principles and mathematical concepts into computational models of living systems. This hands-on guide uses a case study approach organized around central questions in the life sciences, introducing landmark advances in the field while teaching students--whether from the life sciences, physics, computational sciences, engineering, or mathematics--how to reason quantitatively in the face of uncertainty.brpulliDraws on real-world case studies in molecular and cellular biosciences, organismal behavior and physiology, and populations and ecological communitiesliliEncourages good coding practices, clear and understandable modeling, and accessible presentation of resultsliliHelps students to develop a d

Quantitative Biosciences Companion in R | Weitz Joshua S. | Twarda

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pHow can music withstand the death and destruction brought on by war Global conflicts of the 20th century fundamentally transformed not only national boundaries, power relations, and global economies, but also the arts and culture of every nation involved. An important, unacknowledged aspect of these conflicts is that they have unique musical soundtracks. iMusic in World War IIi explores how music and sound took on radically different dimensions in the United States and Europe before, during, and after World War II. Additionally, the collection examines the impact of radio and film as the disseminators of the war's musical soundtrack. Contributors contend that the European and American soundtrack of World War II was largely one of escapism rather than the lofty, solemn, heroic, and celebratory mode of war music in the past. Furthermore, they explore the variety of experiences of populations forced from their homes and interned in civilian and POW camps in Europe and the United States, 

Music in World War II | Potter Pamela M. | Twarda

ENdisc.pl

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hands on programming with r