Report Writing for Data Science in R

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Report Writing for Data Science in R

Report Writing for Data Science in R

Roger D. Peng

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श्रेणियाँ:

Computers - Lectures, monographs

साल:

2015

भाषा:

english

पृष्ठ:

120

फ़ाइल:

PDF, 7.73 MB

IPFS:

,

english, 2015

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आप के लिए दिलचस्प हो सकता है

Indira Cavagnaro — The Big Book of Python for Data Analysis: Learn Data Science and Coding With Python

Campbell, Alex [Campbell, Alex] — Data Science for Beginners: Comprehensive Guide to Most Important Basics in Data Science

Roger D. Peng — R Programming for Data Science

Jeff Leek — The Elements of Data Analytic Style - A guide for people who want to analyze data

Roger D Peng — Exploratory Data Analysis with R

Roger D. Peng & Elizabeth Matsui — The Art of Data Science: A Guide for Anyone Who Works with Data

Brian Caffo — Statistical Inference for Data Science - A Companion to the Coursera Statistical Inference Course

Roger D. Peng — Exploratory data analysis with R

Roger D. Peng — Exploratory data analysis with R

Roger D. Peng — Report writing for data science in R

Roger D. Peng, Sean Kross, Brooke Anderson — Mastering software development in R

Roger D. Peng, Elizabeth Matsui — The Art of Data Science: A Guide for Anyone Who Works with Data

Jared P. Lander — R for Everyone: Advanced Analytics and Graphics

Jennifer Jane Stirrup, Ruben Oliva Ramos — Advanced Analytics with R and Tableau

Michael Freeman, Joel Ross — Programming Skills for Data Science: Start Writing Code to Wrangle, Analyze, and Visualize Data with R, First Edition

Victor Eijkhout — The computer science of TeX and LaTeX

Arindama Singh — Logics for Computer Science, 2nd Edition

Brian Caffo — Regression Models for Data Science in R A companion book for the Coursera Regression Models class

— Literate Programming

Donald E. Knuth — Literate programming

Nathan Carter — Data Science for Mathematicians

Paula Moraga — Geospatial Health Data-Modeling and Visualization with R-INLA and Shiny

Chester Ismay, Albert Y. Kim — Statistical Inference via Data Science: A ModernDive into R and the Tidyverse (Chapman & Hall/CRC The R Series)

Ewen Harrison & Riinu Pius — R for Health Data Science

Maria L. Rizzo — Statistical computing with R

Ronald K. Pearson — Exploratory Data Analysis Using R

Michael J. Crawley — The R Book

Frees, Edward W — Regression modeling with actuarial and financial applications

Edward W. Frees — Regression Modeling with Actuarial and Financial Applications (International Series on Actuarial Science)

Carl Shan, Henry Wang, William Chen; Max Song — The Data Science Handbook

Knuth D.E. — Literate Programming

Knell, Robert J — Introductory R: A Beginner's Guide to Data Visualisation, Statistical Analysis and Programming in R

Robert Kabacoff — Modern Data Visualization with R (Chapman & Hall/CRC The R Series)

Bernd Bischl, Raphael Sonabend, Lars Kotthoff, Michel Lang — Applied Machine Learning Using mlr3 in R

Mark J. Bennett, Dirk L. Hugen — Financial Analytics with R. Building a Laptop Laboratory for Data Science

Graham J. Williams — The Essentials of Data Science: Knowledge Discovery Using R

Paola Zuccolotto; Marica Manisera — Basketball Data Science: With Applications in R

Linda Null — Advanced Computer Organization (custom edition)

Leisch, Friedrich; Peng, Roger D.; Stodden, Victoria — Implementing Reproducible Research

Roger Peng — R Programming for Data Science

Roger D. Peng, Elizabeth Matsui — The Art of Data Science

Brian Caffo, Roger D. Peng, Jeffrey T. Leek — Executive Data Science: A Guide To Training And Managing The Best Data Scientists

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