Statistical Analysis with Stata and R Training Course
Stata is a general-purpose software package written in C. R is a programming language and software environment for statistical computing. Using Stata and R, users can analyze large data sets for use cases such as economics, sociology, biomedicine, etc.
This instructor-led, live training (online or onsite) is aimed at data analysts who wish to use Stata and R to analyze big data for statistical analysis.
By the end of this training, participants will be able to:
- Create statistic models for predicting key interest variables and events.
- Generate descriptive visualizations, summary tables, frequencies, and more.
- Manage and structure large databases to preapare for data analysis.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Course Outline
Introduction
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
Requirements
- An understanding of data analysis
Audience
- Data Analysts
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Course - Statistical Analysis with Stata and R
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