Research Skills
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Getting Started
Pre-term preparation
Python to R reference
Git troubleshooting
Classroom 50
Individual repo (Weeks 1–4)
Drax briefing repo (Weeks 3–4)
Group repo (Weeks 5–10)
Report repo (Weeks 7–10)
Reference
The scientific method
Carbon accounting summary
AI, reproducibility & integrity
Chart audit (Week 2 homework)
Bias bingo (Week 7 homework)
Guides
Briefing structure guide
Writing in Markdown
Peer review template
Project topics
Assessment brief
External links
webR
More or Less
The Economist
Slides
Phase 1: Biomass Mini-Project
Week 1: What makes a good question?
Week 1: Meet the data (and Git)
Week 2: What do the numbers say?
Week 2: Making the biomass case
Week 3: How confident should we be?
Week 3: Changing the assumptions
Week 4: Making the case
Week 4: Write, review, reveal
Phase 2: Your Project
Week 5: Designing your investigation
Week 5: Planning your investigation
Week 6: Testing hypotheses
Week 6: First tests
Week 7: Comparing groups
Week 7: Deepening your analysis
Week 8: Models and their limits
Week 8: Fitting and breaking models
Week 9: AI, reproducibility, and integrity
Week 9: AI as critic
Week 10: Bringing it together
Week 10: Review, revise, submit
Exercises
Phase 1: Biomass Mini-Project
Week 1: Meet the data
Week 2: Dodgy plots
Week 2: Your first ggplot
Week 2: Making the biomass case
Week 3: Changing the assumptions
Phase 2: Your Project
Week 5: Designing your investigation
Week 5: Planning your investigation
Week 6: Testing hypotheses
Week 6: t-test workflow
Week 7: Comparing many groups
Week 7: Effect sizes
Week 8: Models and their limits
Week 8: Fitting and breaking models
Week 9: AI and reproducibility
Week 9: Checking your work
Week 10: Common pitfalls
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