Cookbook for R JavaScript Tutorial Code School vs Treehouse vs Codecademy: A Review | Mike LaPeter I’m so thankful for all 3 of these companies. They’ve all been a huge help in my path from total hack to advanced-beginner rubyist. After spending so much time on all 3 sites, I thought the time had come to share my thoughts to help anyone out there who may not have time to fully devote to all 3. They’ve all got strengths and weaknesses, and each seems more targeted for a specific learner. I’ve spent quite a bit of time on each, and you can see my profiles here: View Code School Courses I’ve Taken View Treehouse Courses I’ve Taken [Inactive] View Codecademy Courses I’ve Taken In this first post, I’ll cover Code School in-depth, followed by Treehouse and Codecademy in later posts. Monthly Cost: $25.00 Ruby Courses Available (as of 1/10/13): 8 Best For: Advanced Beginners and Above I’ll come right out and say it: I love Code School. Code School Strengths: Incredibly High Production Values: Every class is extremely well done. Code School Weaknesses Code School Review:
alyssa frazee Thu 02 January 2014 | -- (permalink) My sister is a senior undergraduate majoring in sociology. She just landed an awesome analyst job for next semester and was told she'll be using some R in the course of her work. She asked me to show her the ropes during winter vacation, and of course I said yes! One catch: the day we planned to work, it turned out we only had an hour of overlapping free time. Challenge accepted. (1) download R and RStudio I'm impressed that RStudio is both accessible/helpful for beginners and useful for experts. (2) console and script The first thing we did after getting set up was type two lines into the console: It wasn't exactly "hello world", but it illustrated some concepts like "assignment" and "variables" and "evaluation"2. The next thing I had my sister do was save those two lines of code in an R script. (3) comments # COMMENTS ARE SUPER IMPORTANT so we learned about them (4) graphics x = rnorm(1000, mean = 100, sd = 3) hist(x) (5) getting help (6) data types vectors
Developer Network · R Tools for Visual Studio Welcome to R Tools for Visual Studio Preview! About this release THANK YOU for trying out this second preview release of R Tools for Visual Studio (RTVS)! We welcome your feedback and comments; we’re actively monitoring our Github issue tracker and triage new incoming issues every Friday. Of course, we remind you that this release is meant for evaluation purposes only and not for production use. If you already have VS2015 with Update 1 (or higher) installed and R installed, you can download RTVS from the link below - but we highly recommend following the Installation guide: Download R Tools for Visual Studio Meet the RTVS Engineering Team in New York City on May 12! Are you in the NYC area on May 12th? If interested, please sign up here. Key features in Version 0.3 For an overview of what is new in 0.3, please see our What’s New in 0.3 page. Completely New Features for 0.3 Existing and Improved Features A quick video overview Installation and first steps The pre-requisites for RTVS are: Q. A. Q. A.
Starting data analysis/wrangling with R: Things I wish I'd been told October 14, 2014, [MD] R is a very powerful open source environment for data analysis, statistics and graphing, with thousands of packages available. After my previous blog post about likert-scales and metadata in R, a few of my colleagues mentioned that they were learning R through a Coursera course on data analysis. I have been working quite intensively with R for the last half year, and thought I'd try to document and share a few tricks, and things I wish I'd have known when I started out. I don't pretend to be a statistics whiz – I don't have a strong background in math, and much of my training in statistics was of the social science "click here, then here in SPSS" kind, using flowcharts to divine which tests to run, given the kinds of variables you wanted to compare. So here are some of my suggestions and "lessons learnt", in no particular order. RStudio is an great open source integrated development environment for R. There are lot's of R textbooks and documentation out there.
R Moves Up From #9 to #6, But What Does It Mean to Really be Proficient in a Language? There's been a lot of noise in the data science community this past week about IEEE Spectrum's 2015 language rankings, where R moved up three notches from #9 in 2014 to #6 in 2015. The Spectrum post gives some lip service to needing to know a domain in addition to just the language itself. But here I drill down into what it means to really know a language. API for the standard library. So, do you really know R?
Find Your Profitable Course Idea | TNW Academy Over the past few years, I’ve intensely studied the best online course creators who've shown you can teach on almost any subject. Eventually, using the process I learned, I launched my own course to create a batch of happy students across the world and generate over $50,000 revenue in a single month. This email course is the result of my personal studies and the lessons I've learned helping some of Fedora's growing set of independent teacher entrepreneur who already work with almost half a million online students. Looking forward to having you inside! Lesson 1 How to choose your course idea (even if you think you don’t have any profitable ideas right now). Lesson 2 How to really figure out what your audience wants (without asking them directly). Lesosn 3 How to differentiate your course from other paid offerings and free content out there. Lesson 4 How to map out amazing content that matches up exactly with what your audience wants. Lesson 5 Lesson 6 Lesson 7
Inicio LIBROS RECOMENDADOS PARA APRENDER ESTADÍSTICA CON R - Blog Estadística & R Hoy vengo con una lista de libros recomendados para leer en cualquier momento de tu carrera profesional porque son algunos de los mejores y más leídos libros de Estadística con R. Todos los libros que te enseño son excelentes, no hay un orden de importancia, pero sí hay diferencias en la complejidad de cada uno. Voy a comentarte cada libro para que sepas si está hecho para ti. Es un curso de Estadística básica con R que logra su objective, es rápido y una buena referencia para comenzar. Libro de R básico que se divide en pequeños pasos orientados a la realización de tareas. Es una introducción al lenguaje R y cómo utilizarlo para el análisis estadístico y gráfico. R for Beginners de Emmanuel Paradis The R Book de Michael J. Una guía extensa sobre la estadística aplicada en R, puedes encontrar de todo en este libraco. A first course in statistical programming with R de W.J. Es una buena introducción para emperzar a programar en R. A Beginner´s Guide to R de Alan Zuur Muy bueno.
bookdown: Easy Book Publishing with R Markdown