Course Outline


Stata and Big Data

  • What is Stata?
  • Stata syntax and commands

R Programming

  • What is R?
  • R syntax and structure

Preparing the Development Environment

  • Installing and configuring Stata
  • Installing and configuring R libraries and frameworks

R and Stata

  • Reading and writing to Stata with R

Databases and Data in Stata

  • Opening and clearing databases
  • Compressing databases
  • Importing and exporting databases
  • Viewing, describing, and summarizing raw data
  • Using tabulations and tables
  • Implementing variables for data manipulation

Descriptive Analysis and Predictive Analysis

  • Working with distributional analysis
  • Working with Monte Carlo simulations
  • Working with count data analysis
  • Working with survival analysis

Hypothesis Testing

  • Testing and comparing means

Graphing in Stata

  • Using plots, charts, and graphs
  • Working with statistical analysis in graphing
  • Styling and combining graphs

Regression Models with R

  • Using bivariate correlation and regression
  • Working with OLS regression, logits, and probits
  • Using interactive effects in regression models

Summary and Conclusion


  • An understanding of data analysis


  • Data Analysts
  35 Hours


Related Courses

Algorithmic Trading with Python and R

  14 hours

Stata: Beginner to Advanced

  14 hours

Programming with Big Data in R

  21 hours

Marketing Analytics using R

  21 hours

Introduction to R

  21 hours

Neural Network in R

  14 hours

Advanced R Programming

  7 hours

Building Web Applications in R with Shiny

  7 hours

Data Mining with R

  14 hours

Introductory R for Biologists

  28 hours

Forecasting with R

  14 hours

R for Data Analysis and Research

  7 hours


  21 hours

Machine Learning Fundamentals with R

  14 hours

Introduction to Data Visualization with Tidyverse and R

  7 hours