WHO Member State metadata | Checking availability before fetching | Fetching indicator data from GHO | Step 1: Search for an indicator | Step 2: Fetch the data | Step 3: Clean the raw response | Aggregating indicators with geomean() | Plotting with theme_dsi() and theme_dsi_facet() | Single panel: theme_dsi() | Faceted: theme_dsi_facet() | Tables with dsi_flextable_defaults() | Working with SDG indicators | Keeping named SDG dimensions | Showing dimension meaning and source context | Combining GHO and SDG with bind_indicators() | Exploring series with sdg_coverage() | Where to next

Discover GHO codes and preserve named dimensions | Discover GHE selections | Download selected measures | Reproducible pulls and revised estimates | WHO 2026 standard population

1. Import and inspect | 2. Compare missing-data choices | 3. Investigate outliers | 4. Standardize text labels | 5. Check keys before merging | 6. Visualize a decision | 7. Debrief and test understanding

Install and launch | Your first learning session | The module map | Work with your own files | Use the AI pages | Common questions

Match the modules to a learning goal | A three-hour data science session | A two-hour AI session | Prepare the room and computers | Facilitate a 20–30 minute lab | Practise a prompt with explicit checks | Critique an AI-generated analysis | Use the quiz to support discussion | Close with an analysis record

Observed, expected and excess deaths | Aggregate the numerator and denominator | Review the baseline first | The model menu | Use the Best Fit tab carefully | Read uncertainty in context | Compare sensitivity and explain the finding | Save a reproducible record

Install and launch | A first analysis with built-in data | 1. Load an example | 2. Check what was loaded | 3. Run a small model comparison | 4. Read the results | 5. Save the analysis | Prepare your own workbook | Report requirements | Troubleshooting

Start from a supplied template | Preserve the mortality sheet layout | Understand the processed table | Edit the event calendar | Decide what the baseline contains | Upload, merge and verify | Check a downloaded processed table in R

Example data | Trend lines with a confidence band | Breakdowns from dim1 / dim2 / dim3 | Forest-style country comparison | Dumbbell progress plot | Tracking progress with aarr()