curso de R

30 Setembro 2018, 19:08 • Vítor Sousa

Dear students,

the course will start tomorrow, 01.10.2018 at 14h00 in room 2.3.37. 
You can use the computers in room 2.3.37 or bring your own laptop. If you bring your laptop you will need to install R and RStudio (please see instructions below).
We will use swirl() tutorials during the course. If you bring your laptop you should follow the steps below to install the swirl() package, but we will also do this in class in case you have problems. 

The course materials will be available on a shared dropbox folder. Please download the slides and course materials for each day from the following link:https://www.dropbox.com/sh/vvtvsp98eavu421/AABwHJJlLnmWutkSO-5AfaJ3a?dl=0

1. Install R and Rstudio

R and Rstudio work in different platforms (Linux, Windows, Mac).

Please install R from https://www.r-project.org/
Follow the instructions to install it in your system.

Please install Rstudio from https://www.rstudio.com/ 

Download the Rstudio desktop Open source license https://www.rstudio.com/products/rstudio/download/

2. Swirl Intro tutorials

Swirl provides several interactive tutorials to learn how to use R. I recommend that you follow this before the course to get familiar with the R environemnt. Just follow the following steps

In RStudio console type:

install.packages("swirl")

For Linux users you might need to update a few libraries in your system. Install them using the following commands in your terminal.

sudo apt-get install libcurl4-openssl-dev
sudo apt-get install libssl-dev

After installing the package swirl, you can start the tutorials.

library("swirl")
swirl()

After asking for you name (anything you wish), it will print something like:

To begin, you must install a course. I can install a course for you from the internet, or I can send you to a web page (https://github.com/swirldev/swirl_courses) which will provide course options and directions for installing courses yourself. (If you are not connected to the internet, type 0 to exit.)
1: R Programming: The basics of programming in R
2: Regression Models: The basics of regression modeling in R
3: Statistical Inference: The basics of statistical inference in R
4: Exploratory Data Analysis: The basics of exploring data in R
5: Don't install anything for me. I'll do it myself.