R Programming 8 Lessons 0 Free R programing language, handles statistical computation of information and graphical representations. Lessons INTRODUCTION TO DATA ANALYTICS Business Analytics and R Understand the use of ‘R’ in the industry Compare R with other softwares in analytics Install R and the packages from CRAN Perform basic operations in R using command line Introduction to R Studio User Interface of RStudio - The R IDE Basic Building Blocks in R Sequence of Numbers in R Understanding Vectors in R Handling Missing Values in R Subsetting Vectors in R Matrices and Data Frames in R Logical Statements in R Using the Lapply, sapply, vapply and tapply Functions R BASICS Understanding R data structure Variables & Data Types Various Operators like Arithmetic, Relational, Logical, Assignment Scalars Vectors Arrays Matrices List Data frames Using c, Cbind,Rbind, attach and detach functions in R Factors Loops including control statements Manipulating and formatting strings String-Manipulation Functions - Using nchar(), toupper(), tolower(), substring() functions on strings User defined functions: Invoking functions with and without passing parameter DATA IMPORT & MANIPULATION Importing data Reading Tabular Data files Reading CSV files Importing data from excel R Assignment Operators Accessing database Saving in R data Loading R data objects Writing to files Manipulating Data Selecting rows/observations Selecting columns/fields Merging data Relabelling the column names Converting variable types Data sorting Data aggregation K-Means Clustering use for EXPORATORY DATA ANALYSIS Understanding the Exporatory Data Analysis(EDA) Implementation of EDA on various datasets Boxplots Understanding the cor() in R EDA functions like summarize(), list() Multiple packages in R for data analysis The Fancy plots like Segment plot R PROGRAMMING Control Structures While loop If loop For loop Arithmetic operations Writing Simple Programs Writing Complex Programs R functions Commonly used Mathematical Functions Commonly used Summary Functions Commonly used String Functions User defined functions local and global variables ADVANCED CONCEPTS DATA VISUALIZATION IN R Understanding on Data Visualization Graphical functions present in R Plot various graphs like tableplot Histogram Boxplot, line chart Customizing Graphical Parameters to improvise the Plots Understanding GUIs like Deducer and R commander Introduction to Spatial Analysis Scatterplot Developing graphs Live Project Case Studies etc. Statistical Distributions Finding mean, median & mode of data in a vector Establishing relationship model between two variables using linear regression Establishing relationship model between more than two variables using multiple regression Designing a regression model for categorical values using logistic regression Normal Distribution Binomial Distribution Poisson distribution Analysis of Covariance Using ts() to create, manipulate and plot the data for time series analysis Using party() to create Decision Tree to represent choices and their results in form of a tree Creating and analyzing Random Forest Using Survival Analysis for predicting an occurrence of an event Using Chi Square tests to determine correlation between categorical variables DEBUGGING Fundamental Principles of Debugging Why Use a Debugging Tool? Using R Debugging Facilities Ensuring Consistency in Debugging Simulation Code Syntax and Runtime Errors
INTRODUCTION TO DATA ANALYTICS Business Analytics and R Understand the use of ‘R’ in the industry Compare R with other softwares in analytics Install R and the packages from CRAN Perform basic operations in R using command line Introduction to R Studio User Interface of RStudio - The R IDE Basic Building Blocks in R Sequence of Numbers in R Understanding Vectors in R Handling Missing Values in R Subsetting Vectors in R Matrices and Data Frames in R Logical Statements in R Using the Lapply, sapply, vapply and tapply Functions
R BASICS Understanding R data structure Variables & Data Types Various Operators like Arithmetic, Relational, Logical, Assignment Scalars Vectors Arrays Matrices List Data frames Using c, Cbind,Rbind, attach and detach functions in R Factors Loops including control statements Manipulating and formatting strings String-Manipulation Functions - Using nchar(), toupper(), tolower(), substring() functions on strings User defined functions: Invoking functions with and without passing parameter
DATA IMPORT & MANIPULATION Importing data Reading Tabular Data files Reading CSV files Importing data from excel R Assignment Operators Accessing database Saving in R data Loading R data objects Writing to files Manipulating Data Selecting rows/observations Selecting columns/fields Merging data Relabelling the column names Converting variable types Data sorting Data aggregation
K-Means Clustering use for EXPORATORY DATA ANALYSIS Understanding the Exporatory Data Analysis(EDA) Implementation of EDA on various datasets Boxplots Understanding the cor() in R EDA functions like summarize(), list() Multiple packages in R for data analysis The Fancy plots like Segment plot
R PROGRAMMING Control Structures While loop If loop For loop Arithmetic operations Writing Simple Programs Writing Complex Programs R functions Commonly used Mathematical Functions Commonly used Summary Functions Commonly used String Functions User defined functions local and global variables
ADVANCED CONCEPTS DATA VISUALIZATION IN R Understanding on Data Visualization Graphical functions present in R Plot various graphs like tableplot Histogram Boxplot, line chart Customizing Graphical Parameters to improvise the Plots Understanding GUIs like Deducer and R commander Introduction to Spatial Analysis Scatterplot Developing graphs Live Project Case Studies etc.
Statistical Distributions Finding mean, median & mode of data in a vector Establishing relationship model between two variables using linear regression Establishing relationship model between more than two variables using multiple regression Designing a regression model for categorical values using logistic regression Normal Distribution Binomial Distribution Poisson distribution Analysis of Covariance Using ts() to create, manipulate and plot the data for time series analysis Using party() to create Decision Tree to represent choices and their results in form of a tree Creating and analyzing Random Forest Using Survival Analysis for predicting an occurrence of an event Using Chi Square tests to determine correlation between categorical variables
DEBUGGING Fundamental Principles of Debugging Why Use a Debugging Tool? Using R Debugging Facilities Ensuring Consistency in Debugging Simulation Code Syntax and Runtime Errors
