COURSE OBJECTIVES

Design and run statistical analysis workflows in R and RStudio.
Produce high-quality scientific graphs and visualizations.
Apply parametric and non-parametric methods, including hypothesis testing and multiple comparisons.
Perform regression and ecological modelling with diagnostics, confidence intervals, and predictions.
Prepare scientific reports that interpret and communicate statistical findings

KEY TOPICS

• Statistical analysis workflows in R
• Scientific visualization and graphical presentations
• Parametric and non-parametric statistical methods
• Hypothesis testing and interpretations
• Regression and ecological modelling
• Statistical diagnostics and model evaluation
• Multiple comparison procedures
• Confidence intervals and prediction analysis
• Scientific reporting and interpretation of results

LEARNING OUTCOMES

By the end of the course participants will be able to:

• Conduct statistical analyses in R and RStudio using real-world datasets.
• Generate high-quality statistical graphs and visualizations.
• Select and apply appropriate parametric and non-parametric methods.
• Perform hypothesis testing, multiple comparisons, and regression analyses with proper diagnostics.
• Build ecological models and interpret confidence intervals and predictions.
• Interpret and communicate statistical findings effectively.
• Prepare scientific reports supported by sound statistical evidence

TARGET PARTICIPANTS

Postgraduate students from all disciplines. Researchers. University lecturers and academic staff. Data scientists. Environmental and biological professionals. Data analysts interested in ecological applications. NGOs, CSOs, and development practitioners.

Offered By : Institute of Development Studies - Directorate of Public Services

OTHER DETAILS

Course Timeline 4 days
Starting at: 24/11/2026 , ends at: 27/11/2026
Cost: 540,000

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