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R Programming – A Practical Approach

R Programming – A Practical Approach

R Programming – A Practical Approach

About the course

This course on R programming will transform the learners to quality data analysts and data researchers, who can contribute to the field of data and statistical analysis. This course focussed more on practical learning rather than theoretical. Dealing with concrete datasets and analysis of data has made this course unique with quality course content matching the current industry requirements. This course comprises of video lectures which can be viewed online and offline as per the convenience of the user. It also practice questions, downloadable source code files for user's future reference, which makes it all together a complete package with study material.

This course has been designed keeping in mind, the needs of analysts and data researchers who wish to cater to their most difficult issues in the fields running from computational science to extensive marketing using R programming. In this course, the user will be able to learn to use datasets and create analytical charts like Bar graphs, pie charts, histograms, box plots, 3D scatter plots etc. The users taking this course will be benefitted, as they’ll be able to work with datasets and produce detailed analysis reports simply by using R programming. R programming is very interesting language and is used in most of the fields. However the popular ones include - Finance, Bio Science, Supply chain, Sports, Retail, Marketing and Manufacturing. SInce this language has a wide area of application, it’s worth having a go at it.


Advantages of learning this course
Target Audience
Why learn R?
Course Features
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Other Information


*CGPA to percentage conversion formula:

Equivalent Percentage = CGPA obtained X 9.5 X (10/CGPA Scale)
Example: If CGPA obtained is 8.00 on the scale of 10, then Equivalent
percentage will be 8.00 X 9.5 X (10/10) = 76%,
or If CGPA is 3.7 out of 4, then Equivalent percentage will be 3.7 X 9.5 X (10/4) = 87.88%


We urge you to provide correct information to your best knowledge. Certificates will be withheld if found that you have misrepresented any data / information.


  1. R- Basics

    1. Steps to Install 'R'

    2. R-Studio Installation

    3. Using R Materials

    4. R-Studio Interface

    5. Steps to Install Packages

    6. Default Data-Sets in R

    7. Manual Data Entry

    8. Data Importing

    9. Tabular to Row Data Conversion

    10. R - Colors

    11. Overview - 'Colorbrewer'

    12. Colors in R: Summary

  2. Introduction to Charts

    1. Bar Charts

    2. Pie Charts

    3. Histograms

    4. Box-Plots

    5. Customized Graphs

    6. Images

    7. Layering Plots: Summary

  3. Introduction to Statistics

    1. Frequencies

    2. Descriptives

    3. Single Proportion Testing

    4. Single Mean Testing

    5. Chi-Square Test

    6. Univariate Analysis

    7. Descriptive Statistics: Summary

  4. Manipulating Data

    1. Outliers

    2. Transformation of Variables

    3. Composite Variables

    4. Working with Missing Data

    5. Working with Outliers: Summary

  5. Managing Huge Data

    1. Working with Cases

    2. Working with Subgroups

    3. Working with Files - Merging

    4. Working with Subgroups: Summary

  6. Association: Presentation

    1. Bar Charts

    2. Box Plots

    3. Scatter Plots

    4. Working with Plots: Summary

  7. Associations: Statistics

    1. Correlation

    2. Bivariate Regression

    3. T-Test

    4. Paired T-Test

    5. ANOVA

    6. Proportions

    7. Chi-Square Test

    8. Statistics for Bivariate Associations

    9. Association Stats: Summary

  8. Advanced Charts

    1. Bar Charts for Mean

    2. Scatter Plots for Grouped Data

    3. Scatter Plot Matrices

    4. 3D Scatter Plots

    5. Charts for Multiple Variables: Summary

  9. Multiple Variable Statistics

    1. Multiple Regression

    2. Two-Factor ANOVA

    3. Cluster Analysis

    4. Principal Component / Factor Analysis

    5. Multiple Variable Statistics: Summary

  10. R Programming Final Quiz