R Programming 2: Data Analysis
R has become the world-wide language for statistics, predictive analytics, and data visualization. It offers the widest range available of methodologies for understanding data, from the most basic to the most complex and bleeding edge. In our second workshop with R, you will have the opportunity to learn basic data manipulation and wrangling techniques, basic statistical inference and also implement a few machine learning models. This workshop aims to introduce basic techniques that data scientists or analysts use in everyday tasks. Basic data manipulation will help you prepare your data for statistical analysis. Statistical inference helps you derive conclusions from your data and machine learning models helps you predict the future! But only to a certain degree!
- Data cleaning.
- Exploratory data analysis.
- Probability distributions.
- Hypothesis testing.
- Analysis of variance.
- Linear regression.
- Logistic Regression.
Prerequisites: Familiarity with R concepts (Data frames, matrices, vectors, basic functions). Knowledge of basic statistical concepts(variance, standard deviation,probability distributions) is a plus point but not necessary.
Presenter: Shourya Paranjape, Graduate Research Assistant for Research Data Services
IMPORTANT - Please bring your own laptop to the workshop with R already installed.
Install R & RStudio in Windows
- Download R from http://cran.us.r-project.org/ (click on “Download R for Windows” > “base” > “Download R 3.x.x for Windows”)
- Install R. Leave all default settings in the installation options.
- Download RStudio from http://rstudio.org/download/desktop and install it. Leave all default settings in the installation options.
- Open RStudio.