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Course Outline
Introduction to Stata
- Overview of Stata and its applications.
- Comparison of Stata with SPSS and R.
- Stata syntax, commands, and workflows.
Setting Up the Environment
- Installing and configuring Stata.
- Review of RStudio and R libraries for integration.
Data Management in Stata
- Importing and exporting data.
- Data cleaning and transformation.
- Managing large datasets efficiently.
Stata for Statistical Analysis
- Descriptive statistics and summary tables.
- Probability distributions and hypothesis testing.
- Regression analysis: linear, logistic, and multivariate models.
Graphing and Visualization in Stata
- Creating charts, plots, and graphs.
- Customizing visualizations for reports.
Stata and R Integration
- Reading and writing data between Stata and R.
- Calling Stata commands from R.
- Automating statistical workflows between the two tools.
Advanced Topics
- Macros and loops in Stata.
- Using Stata for predictive modeling.
- Programming in Stata (do-files, ado-files).
Case Studies and Practical Applications
- Real-world applications in research and data science.
- Integrating Stata with R in academic and industry projects.
Summary and Next Steps
Requirements
- Experience using SPSS for statistical analysis
- Proficiency in R programming
Audience
- Computer science professionals
- Data scientists and researchers working with statistical models
- Analysts looking to integrate Stata with R
35 Hours
Testimonials (5)
Data management, reporting and statistics concepts.
Dumisani - Interfront SOC Ltd
Course - Stata: Beginner to Advanced
The pace was just right and the relaxed atmosphere made candidates feel at ease to ask questions.
Rhian Hughes - Public Health Wales NHS Trust
Course - Introduction to Data Visualization with Tidyverse and R
Michael the trainer is very knowledgeable and skillful about the subject of Big Data and R. He is very flexible and quickly customize the training meeting clients' need. He is also very capable to solve technical and subject matter problems on the go. Fantastic and professional training!.
Xiaoyuan Geng - Ottawa Research and Development Center, Science Technology Branch, Agriculture and Agri-Food Canada
Course - Programming with Big Data in R
I enjoyed the Excel sheets provided having the exercises with examples. This meant that if Tamil was held up helping other people, I could crack on with the next parts.
Luke Pontin
Course - Data and Analytics - from the ground up
The flexible and friendly style. Learning exactly what was useful and relevant for me.
