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Duration 35 hours
Course Outline
Introduction
Stata and Big Data
- Overview of Stata.
- Exploring Stata syntax and command structures.
R Programming
- Introduction to R.
- Understanding R syntax and code organization.
Setting Up the Development Environment
- Installation and configuration of Stata.
- Installing and configuring R libraries and frameworks.
Integrating R and Stata
- Data exchange: Reading and writing Stata files using R.
Databases and Data Management in Stata
- Opening and clearing database sessions.
- Compressing database files.
- Importing and exporting data sources.
- Viewing, describing, and summarizing raw data.
- Utilizing tabulations and summary tables.
- Applying variables for data manipulation.
Descriptive and Predictive Analysis
- Analyzing distributional characteristics.
- Conducting Monte Carlo simulations.
- Analyzing count data.
- Performing survival analysis.
Hypothesis Testing
- Testing and comparing statistical means.
Visualization in Stata
- Creating plots, charts, and graphs.
- Incorporating statistical analysis into graphical outputs.
- Styling and combining multiple graphs.
Regression Modeling with R
- Applying bivariate correlation and regression techniques.
- Utilizing OLS regression, logit, and probit models.
- Implementing interactive effects in regression analysis.
Summary and Conclusion
Requirements
- Foundational knowledge of data analysis.
Target Audience
- Data Analysts.
Testimonials (1)
a multitude of points
