Milano R net, in collaboration with Quantide, organizes
Course “Introduction to R”
June 7-8, 2012

Course goals
The course aims to provide an overview of the basic R environment and its applications. This course is intendended as a starting point for any future development with R.
At the end of the course, you will be able to gain awareness of the basic R language, importing/exporting data and manipulate data using R. You will do exploratory data analysis, perform basic statistics and build plots using R.

Who should attend this course
Anyone who is new to R and willing to learn it. Anyone who has some previous knowledge of R and wants to organize it in a more structured way.

Course location
Hotel Michelangelo; Via Scarlatti, 33; Milano (near Central Railway Station)

Course language
Course will be held in Italian. Course material will be in English.

Information and bookings: [email protected]

Course syllabus

1. Introduction to R: overview
   • R History
   • R Features
   • R Commercial Support
   • Installing and Updating R
   • Graphical User Interfaces
   • R Resources: Help, Online Resources, Books
2. R Data Objects
   • Vectors
   • Matrices
   • Lists
   • Factors
   • Data frames
   • Missing Values and Infinite
3. Data Import And Export
   • Importing and Exporting Text Files
   • Importing and Exporting Excel Files
   • Data Base Connection
   • Saving and Loading R Files
4. Data Management
   • Assigning Names to Rows and Columns of Data Frames
   • Extracting Data from Data Frames
   • Sorting Data Frames: order()
   • Attaching Data Frames: attach()
   • Adding or Removing Columns from a Data Frame
   • Merging Data Frames: merge()
   • Combining Data Frames: rbind()
   • Reshaping Data: reshape()
   • Aggregating Data Frames: apply() and aggregate()
5. Using R functions
   • Basic Mathematical Functions
   • Character Manipulation Functions
   • Apply functions to a Data Frame: apply family
   • Basic Probabilistic Function
   • Basic Statistics Function
   • Writing a Function
6. R Graphics
   • The Graphics Environment
   • Scatter Plot
   • Low-level Functions
   • Histograms, Barplot, Boxplot and Three Dimensional Plots
   • Introduction to Alternative Graphic Systems: lattice and ggplot
7. Introduction to Statistical Models with R
   • Linear Regression Models
   • ANOVA Models