Advanced R Programming for Statistical Analysis Mastery

Course Content:

Introduction to Statistics – Descriptive Statistics, Summary Statistics Basic probability theory
Statistical Concepts ( uni-variate and bi-variate sampling, distributions, re-sampling, statistical Inference, prediction error)
Probability Distribution (Continuous and discrete-Normal, Bernoulli, Binomial, Negative Binomial, Geometric and Poisson distribution)
Bayes’ Theorem
Central Limit Theorem
Data Exploration & preparation Concepts of Correlation
Regression
Covariance
Outliers etc.

Introduction & Installation of R
R Basics
Finding Help
Code Editors for R
Command Packages
Manipulating and Processing Data in R
Reading and Getting Data into R
Exporting Data from R
Data Objects- Data Types & Data Structure
Viewing Named Objects
Structure of Data Items
Manipulating and Processing Data in R ( Creating, Accessing, Sorting Data Frames, Extracting, Combining, Merging, Reshaping Data Frames)
Control Structures, Functions in R (numeric, character, statistical)
Working with objects
Viewing Objects within Objects
Constructing Data Objects
Building R Packages
Running and Manipulating Packages
Non Parametric Tests – ANOVA
Chi – Square
T – Test
U – Test
Introduction to Graphical Analysis
Using Plots (Box Plots Scatter Plot, Pie Charts, Bar Charts, Line Chart)
Plotting variables
Designing Special Plots
Simple Liner Regression
Multiple Regression

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