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
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: Assumption audit
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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