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Course Content for R-Language


Course Objective

R Language is programmer for statistical analysis. Statistical Analysis plays major role in the Data Analysis. R is support to research and analysis purpose. It is free source software using this we can do machine learning concepts, statistical analysis and deployment to the researcher.

S.No Topic Detailed Syllabus
1 Introduction to R About R, working with tool and explanation
2 Basic Data Types Data types in R(Numeric, Integer, Complex, Logical, Character) and how to use this Data types in R
3 Objects Creating Objects(Vectors, Matrices, Factors, Arrays, Data frames),uses and creating objects
4 Functions and Loops Etc., Creating, accessing function in R
5 Data Preparation Data Coding, Data Cleaning, Identification Outlier, Handling Missing Values
6 Statistics Basics concepts in statistics
7 Regression & Types of Regression Linear Regression, Multiple Regression , Logistic Regression
8 Classification Methods Discriminant Analysis – Basics, Rotation Methods involved in DA.
9 Cluster Analysis Cluster Analysis Basics and real life Examples
10 Analysis of Variance Anova , Manova
11 Survival Analysis Types of Non parametric test in Survival and Cox proportional Hazard Rate Model
12 Time series Forecasting
13 Machine Learning Algorithms and Coding for Concepts in ML
14 Backup Classes Doubts clarification for all Session



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Thanks for your ideas. I would also recommend that beginners look for answers on various programming forums like https://ittutoria.net/install-a-package-in-r/ which may provide basic knowledge or help find the answer.

R programming
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