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Simulation for Data Science with R

Harness actionable insights from your data with computational statistics and simulations using R About This Book * Learn five;

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Quantitative Economics with R

bootstrap is introduced. Causal inference is illuminated using simulation, data graphs, and R code for applications with real economic examples;

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Quantitative Economics with R: A Data Science Approach

of growth related data and models is presented, before the book introduces the reader to time series data analysis with graphs, simulation, and;

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Beginning Data Science in R 4

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist;

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Simulation Modeling & Arena

related website with an Instructor s Solutions Manual, PowerPoint(R) slides, test bank questions, and data sets for each chapter Simulation;

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Hands-On Data Science with R

Use R for efficient data mining, text analytics and feature engineering Become a thorough data science professional with the help of hands-on;

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Data Science for Business With R

Data Science for Business with R focuses on the concepts foundational for students starting a business analytics or data science course;

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R 4 Data Science Quick Reference

data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications Visualize data with;

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R 4 Data Science Quick Reference

then transform that data using magrittr and dplyr Write functions with R for data science, data mining, and analytics-based applications;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Statistical Inference via Data Science: A ModernDive into R and the Tidyverse

Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference;

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Statistics, Data Analysis And Decision Modeling

applications are emphasized throughout the book for business decision-making; a comprehensive database is developed, with marketing, financial, and;

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R Data Science Quick Reference

Write functions with R for data science, data mining, and analytics-based applications Visualize data with ggplot2 and fit data to models using;

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Data Science Using Python and R

. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Those with;

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Beginning Data Science in R 4

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist;

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Maximum Likelihood for Social Science

data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the;

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Maximum Likelihood for Social Science

data as well as counts, duration data, and strategies for dealing with data missingness. By working through examples, math, and code, the;

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Programming Skills for Data Science

, you'll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman;

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A First Course in Statistical Programming with R

, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other;

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Data Science in Education Using R

Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like;

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Data Science in Education Using R

Data Science in Education Using R is the go-to reference for learning data science in the education field. The book answers questions like;

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Python for Programmers

, contemporary examples. These include natural language processing, data mining Twitter (R) for sentiment analysis, cognitive computing with IBM (R;

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Learn R for Applied Statistics

Statistics is a timely skills-migration book that equips you with the R programming fundamentals and introduces you to applied statistics for data;

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Doing Data Science in R

This approachable introduction to doing data science in R provides step-by-step advice on using the tools and statistical methods to carry;

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Discrete-Event System Simulation

tools for dealing with system design in the presence of uncertainty. Proper collection and analysis of data, use of analytic techniques;

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Practical Data Science With R

familiarity with R is a plus. ABOUT THE TECHNOLOGY R is a programming language which is used for developing statistical software programs. Data;

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Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data

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