Data Science Using R Programming

Statistics in business world

• Descriptive statistics
• Inferential Statistics
• Statistical data analysis
• Variables
• Sample and Population Distributions
• Interquartile range
• Central Tendency
• Normal Distribution
• Skewness.
• Boxplot
• Five Number Summary
• Standard deviation
• Standard Error
• Hypothesis

Introduction to Data Analytics

Objectives

Topics

• Business Analytics, Data, Information
• Understanding Business Analytics and R
• Compare R with other software in analytics
• Install R
• Perform basic operations in R using command line

R objects and Data types

Inbuilt Functions of R

• Environment functions
• Statistical Functions
• li>Text Functions
• Mathematical Functions
• Reading Data from R
• Writing Data into R
• Files connection

Control Structure of R

• If
• For
• Repeat
• While
• Next
• Return

Writing Function in R

Loop Function of R

• Lappy
• Tappy
• Split
• Mappy
• Apply

Date and time in R

• Dates in R
• Time in R
• Operation on Dates and Time on R

Basic Graphs in R

• Creating a graph
• Density Plot
• Dot Plot
• Bar Plot
• Line Charts
• Pie Charts
• Box Plot
• Scatter Plot
• Histogram
• Normal QQ Plot

Advance Graphs in R

• Graphical Parameters
• Lattice Graphs
• Combining Plot
• Ggplots Graph
• Probability Graphs
• Correlograms

Predictive modelling in marketing

• Personal loans cross selling
• Life insurance
• Regression
• Variable selection
• Multiple regression
• Logistic regression
• Multi-colinearity

Business Environment with data science

• To implement the statistical solutions that the team comes up with, sound programming and insight generation.
• Communicate the insights using business-friendly presentations
• Actionable insights
• CORRELATION
• Histogram, scatter plot, boxplot

Projects data

Science Case studies

• Facebook
• Data science implementation by Indian authority
• Fraud detection by RBI
• RISK ANALYTICS
• Dealer segmentation