CMSSSEC02M: R-Programming

CMSHSE101M/CMSGSE101M: (Credits:3): 

📘 R LANGUAGE TUTORIAL AND NOTES MODULE WISE FOR STUDENTS

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R Programming                                                                                                               (45 Classes) 

Module 1: Introduction to R Programming        CLICK FOR NOTES             6 Classes                                    

1. Introduction to R 

● Overview of R and its uses in data analysis and statistics. 

● Installing R and RStudio. 

● Introduction to RStudio interface and its components (Console, Source, Environment, Plots, etc.). 

● Understanding the R command prompt. 

● Basic operations: arithmetic operations, logical operations, and comparison operators. ● Data types in R: numeric, integer, character, logical, and factor. 

● Variable assignment and naming conventions. 

2. Data Structures in R 

● Vectors: creation, indexing, and basic functions (length, class, typeof, etc.). 

● Lists: creation, indexing, and subsetting. 

● Matrices: creation, indexing, and operations. 

● Data frames: creation, importing/exporting data, indexing, and subsetting. 

● Factors: creation, levels, and usage in categorical data. 

Module 2: Data Manipulation and Managemen   CLICK FOR NOTES                            10 Classes 

1. Data Import and Export 

● Reading data from CSV, Excel. 

● Writing data to CSV, Excel. 

2. Data Cleaning and Preparation 

○ Handling missing values and duplicates. 

○ Data type conversions. 

○ Renaming columns and rows 

3. Data Transformation 

○ Selecting columns (select), filtering rows (filter), arranging data (arrange). 

○ Mutating and transforming data (mutate, transmute).

 ○ Summarizing data (summarize, group_by). 

Module 3: Data Visualization                                                                                              10 Classes 

1. Introduction to Data Visualization in R 

○ Understanding the basics of data visualization. 

○ Using base R graphics for plotting. 

2. Using ggplot2 for Advanced Visualization 

○ Introduction to the grammar of graphics. 

○ Creating basic plots (scatter plots, line plots, bar plots, histograms).

○ Customizing plots (titles, labels, themes, colors, and scales). 

○ Faceting and multi-plot layouts. 

3. Interactive Visualizations

○ Introduction to interactive plots using plotly and shiny. 

○ Creating basic interactive plots and dashboards. 

Module 4: Statistical Analysis and Modeling                                                                     3 Classes 

● Descriptive Statistics

○ Calculating measures of central tendency (mean, median, mode). 

○ Calculating measures of dispersion (range, variance, standard deviation). 

Module 5: Advanced R Programming                                                                              10 Classes 

1. Control Structures 

○ Conditional statements (if, else, switch). 

○ Looping constructs (for, while, repeat). 

○ Vectorized operations and the apply family of functions (apply, lapply, sapply, tapply, mapply). 

2. Debugging and Error Handling 

○ Debugging tools in R (debug, trace, browser). 

○ Handling errors and warnings (try, tryCatch). 

Simple Programs :                                                                                                                  6 Classes

 1. Write a R program to take input from the user (name and age) and display the values. Also print the version of R installation. 

2. Write a R program to create a sequence of numbers from 20 to 50 and find the mean of numbers from 20 to 60 and sum of numbers from 51 to 91. 

3. Write a R program to multiply two vectors of integers type and length 3. 

4. Write a R program to find Sum, Mean and Product of a Vector, ignore elements like NA or NaN. 

5. Write a R program to list containing a vector, a matrix and a list and give names to the elements in the list.

 6. Write an R program to extract 3 rd and 5 th rows with 1 st and 3 rd columns from a given data frame. 7. Write a R program to sort a given data frame by multiple column(s). 

8. Write a R program to compare two data frames to find the row(s) in the first data frame that are not present in the second data frame. 

9. Write a program to read a csv file and find min, max and range the data in the file in R 

10. Write a program to find Mean, Median and Mode 

Text Books: 

1.William N. Venables and David M. Smith, An Introduction to R. 2nd Edition. Network Theory Limited.2009 

2. Norman Matloff, The Art of R Programming - A Tour of Statistical Software Design, No Starch Press.2011 i

Reference Books:

1.The Book of R,Tilman M. Davies,No Starch Press,1st edition 2.Discovering Statistics Using R,Andy Field,SAGE Publications Ltd,1st edition