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Introduction to Data Science

Introduction to Data Science - Jeffrey S Salz

Introduction to Data Science

An Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, and graduate students coming from a wide range of backgrounds into the world of data science. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using the R programming language and RStudio (R) from the ground up. Short chapters allow instructors to group concepts together for a semester course and provide students with manageable amounts of information for each concept. By taking students systematically through the R programming environment, the book takes the fear out of data science and familiarizes students with the environment so they can be successful when performing advanced functions.





The authors cover statistics from a conceptual standpoint, focusing on how to use and interpret statistics, rather than the maths behind the statistics. This text then demonstrates how to use data effectively and efficiently to construct models, predict outcomes, visualize data, and make decisions.



Ancillaries



Accompanying digital resources provide code and datasets for instructors and learners to perform a wide range of data science tasks.
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261.06Lei

326.33 Lei

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An Introduction to Data Science is an easy-to-read, gentle introduction for advanced undergraduate, and graduate students coming from a wide range of backgrounds into the world of data science. After introducing the basic concepts of data science, the book builds on these foundations to explain data science techniques using the R programming language and RStudio (R) from the ground up. Short chapters allow instructors to group concepts together for a semester course and provide students with manageable amounts of information for each concept. By taking students systematically through the R programming environment, the book takes the fear out of data science and familiarizes students with the environment so they can be successful when performing advanced functions.





The authors cover statistics from a conceptual standpoint, focusing on how to use and interpret statistics, rather than the maths behind the statistics. This text then demonstrates how to use data effectively and efficiently to construct models, predict outcomes, visualize data, and make decisions.



Ancillaries



Accompanying digital resources provide code and datasets for instructors and learners to perform a wide range of data science tasks.
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