Statistical Analysis Methods (using R)

  • Course level: Advanced  
There are no active Semester Schedule for this course   Pre-registar


To be very good data scientists, it is important to know the statistical logic behind any analytics solution that you provide. In this course, you will learn the essentials of statistics in a practical way with real world examples.


To learn the required theories and concepts of statistics
To learn how to prepare your data for statistical analysis
To learn programming in R
To learn how to do exploratory analysis in R
To know how to identify hypothesis in data science projects
To know how to run different statistical tests to do  hypothesis testing
To undestand how to interpret the p-value and confidence interval
To can install and run a program using Hadoop!
To know the best practices on implementing Big Data
To learn how to build a Big Data strategy in your own  organization


Installing R and R-Studio
Data preparation and cleaning methods in R
Data types in R
Categorical data analysis
Introduction to probability
Hypothesis testing
T-Test and Anova test
Inference: p-values and confidence intervals
Descriptive Statistics
Exploratory analysis
Drawing different graphs

Registration fee :
€ 690

Target audience

  • Data Scientists
  • Business Analysts
  • IT staff
  • Computer Science and IT Students


  • Basic knowledge on data analytics
  • Basic programming
  • experience in R