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Data Analysis Course Using Stata

About the Course

Stata is arguably the best software for data management and statistical analysis. It is a fast, powerful, complete, and integrated statistical package. Stata provides everything for data analysis, from data management to basic analysis and advanced analysis. Stata also makes it easy to generate publication-quality, customisable, distinctly styled graphs, including descriptive graphs, regression fit graphs, and more.

The vast family of users of Stata across many disciplines is another reason it is the software of choice. Stata is distributed in more than 150 countries and continues to satisfy the needs of professionals in both research and business.

The course uses a fine blend of interactive discussions, group exercises for every session, and two project reports that simulate real-life scenarios. At the end of the course, you will be able to produce and interpret basic and intermediate descriptive and inferential statistics using Stata. As a result, you will be able to take raw data, clean it, summarise it, analyse it, and take appropriate action. You will also be able to appraise and interpret research publications.

Course Objectives

This course equips participants with four essential skills for conducting rigorous, reproducible data analysis using Stata: 

  • Understand data and learn Stata: The ability to use Stata efficiently for basic and intermediate data analysis. The course will introduce participants to Stata and Stata files, including do-files (which allow for quality control and quick reproducibility of data management and analysis) and log-files (which store data management and analysis outputs). 
  • Data management: Participants will learn to use Stata for data cleaning and management and be able to import other types of data files, e.g. Excel, into Stata. 
  • Descriptive statistics and subgroup analysis: Participants will understand the theory and use of descriptive statistics. They will be able to test for normality and conduct appropriate descriptive statistics in Stata. They will also learn to conduct sub-group (stratified) analysis in Stata.
  • Inferential statistics: They will also be introduced to inferential statistics, including such concepts as confidence intervals, p-values and bivariate inferential statistics (hypothesis testing). The theory behind the statistics will be explained, and they will be able to conduct analysis in Stata and interpret statistical outputs.
  • AI-Assisted and Agentic Data Analysis: Participants will learn how artificial intelligence can support and accelerate the data analysis workflow without replacing sound statistical reasoning. They will learn to use AI tools to generate, explain, review and debug analytical code; explore datasets and identify potential data-quality issues; support the selection and implementation of appropriate analyses; and interpret statistical outputs. Participants will also be introduced to agentic data analysis, where AI agents can undertake multi-step analytical tasks by interacting with data, writing and executing code, reviewing outputs and iteratively refining an analysis.

Course Outcomes

After the training, participants will be able to take raw data collected in their settings, clean,  summarise, and analyse them, and take appropriate action. They will be proficient in descriptive and inferential statistics. Consequently, they will be able to use Stata in their professional work to produce neat, reproducible analyses and graphics. In addition, they will improve their ability to critically review research papers.

Course Content

Day 1: Introduction to Data and Stata
  • Understand how research questions shape data structure and analysis decisions
  • Navigate Stata’s interface and work efficiently using commands, do-files and log files
  • Bring your own data into Stata and export results in formats your workflow requires
  • Combine datasets from multiple sources with confidence
  • Apply systematic data cleaning practices that protect the integrity of your analysis
  • Produce and interpret descriptive statistics and publication-ready graphs
  • Analyse patterns across subgroups and apply findings in a hands-on mini project
  • Calculate and interpret confidence intervals for your estimates
  • Select and apply the right statistical test for categorical data comparisons
  • Introduction to AI-assisted coding
  • Choose between parametric and non-parametric approaches based on your data
  • Interpret measures of effect and take your first steps into multiple regression
  • Introduction to agentic data analysis
Week 1: Introduction to Data and Stata
  • Understand how research questions shape data structure and analysis decisions
  • Navigate Stata’s interface and work efficiently using commands, do-files and log files
  • Bring your own data into Stata and export results in formats your workflow requires
  • Clean and prepare your data systematically before and during analysis
  • Produce descriptive statistics, subgroup summaries and publication-ready graphs
  • Analyse patterns across subgroups and apply findings in a hands-on mini project
  • Calculate, interpret and communicate confidence intervals with precision
  • Understand the landscape of statistical tests and apply the chi-squared test correctly
  • Introduction to AI-assisted coding
  • Apply parametric and non-parametric tests appropriate to your research context
  • Interpret measures of effect and build a foundation for multiple regression analysis
  • Introduction to agentic data analysis

Who Should Attend

  • Researchers

  • Biostatisticians

  • Data analysts

  • Economists

  • HODs

  • Epidemiologist

  • Programme managers

  • Postgraduate students

  • Market researchers

  • Medical researchers

  • Scientists

  • Government officials

Price Includes

In-person:

  • Course attendance 
  • Full refreshments: 
    • Lunch 
    • Welcome tea (tea and pastries) 
    • Two tea breaks (tea and pastries) 
  • Course lecture notes and training manual 
  • Complimentary parking 
  • Certificate of attendance

Virtual: 

  • Access to interactive webinars 
  • Videos for every interactive webinar session 
  • All pre-reading materials 
  • E-Certificate of attendance

Course Details

In-Person
  • 5 days
  • R13,500
Virtual
  • 4 weeks
  • R11,000
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For more details about our services contact:

Dimakatso Mofokeng
info@cesar-africa.com
+27 11 403 1411

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