mjuarez
Macgyver_Juarez
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Ch 12 - Tidy data
From R for Data Science
Ch 11 - Data Import
From R for data science
Ch 10 - Tibbles
From R for Data Science
Ch 9: Introduction
From R for Data Science
Ch 7 - Exploratory Data Analysis
From R for Data Science
Ch 5 - Data transformation
From R for Data Science
Ch 4: Workflow basics
From R for Data Science
Chapter 8 - Sampling, Sampling Methods, and the Central Limit Theorem
From Statistical Techniques in Business and Economics
Chapter 7 - Continuous Probability Distributions
From Statistical Techniques in Business & Economics
Chapter 6: Discrete Probability Distributions
From Statistical Techniques in Business and Economics
Chapter 14: OS facilities
From Intro to R
Chapter 13: Packages
From Intro to R
Chapter 12: Graphical procedures
From Intro to R
Chapter 11: Statistical Models in R
From Intro to R
Chapter 10: Writing your own functions
From Intro to R
Chapter 9: Grouping, loops and conditional execution
From Intro to R
Chapter 7: Reading data from files
From Intro to R
Chapter 6: Lists and data frames
From Intro to R
Chapter 5: Arrays and Matrices
From Intro to R
Chapter 4: Ordered and unordered factors
Chapter 4 from Intro to R
Chapter 3: Objects, their modes and attributes
Chapter 3 from Intro to R
Chapter 2: Simple Manipulations, Numbers & Vectors
Chapter 2 from Intro to R
Chapter 1: Introduction and Preliminaries
Chapter 1 - Introduction and Preliminaries from An Introduction to R - The Comprehensive R archive Network
Chapter_3_Linear_Regression
Topics and exercises related to linear regression (simple and multiple).
Chapter_2_Statistical Learning
Notes and Exercises
An Introduction to Statistical Learning with Applications in R
I. Introduction