Free Data Analysis Tutorial – Statistical Data Analysis Using R

Learn Descriptive and Inferential Statistics, Data Visualization, Hypothesis Testing and Probability Distribution – Free Course

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What you’ll learn

  • About Qualitative, Quantitative, Bivariate and Multivariate Data
  • Descriptive Statistics ie of Mean, Median, Quartiles, Quantiles, Variance and Standard Deviation
  • Correlation and Covariance
  • Applications of Descriptive Statistics on Stock Price Data
  • Probability Distributions
  • Inferential Statistics – Hypothesis Testing
  • Fundamentals of R Programming & Work with RStudio
  • Use Vectors, Matrices, Lists, Data Frames
  • Importing and Handling CSV files
  • Using dplyr Package for Data Wrangling or Handling
  • Data Visualization in R


  • No prior knowledge or technical backgrounds is required


Welcome to this course of Statistical Data Analysis Using R, and become an R Professional which is one of the most favored skills, that employer’s need.

Whether you are new to statistics and data analysis or have never programmed before in R Language, this course is for you! This course covers the Statistical Data Analysis Using R programming language. This course is self-paced. There is no need to rush – you learn on your own schedule.

This course will help anyone who wants to start a rr as a Data Analyst.

This course begins with the introduction to R that will help you write R code in no time. This course will provide you with everything you need to know about Statistics.

In this course we will cover the following topics:

R Programming Fundamentals

Vectors, Matrices & Lists in R

Data Frames

Importing Data in Data Frame

Data Wrangling using dplyr package

Qualitative and Quantitative Data

Descriptive and Inferential Statistics

Hypothesis Testing

Probability Distribution

This course teaches Data Analysis and Statistics in a practical manner with hands-on experience with coding screen-cast.

Once you complete this course, you will be able to perform Data Analysis to solve any complex Analysis with ease.

Author(s): Syed Mohiuddin

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