Measurement & Experimental Science
Representative Sampling, Replication & Controls
Reliable cultivation comparisons require representative sampling and enough replication to separate a treatment effect from natural plant-to-plant variation.
Key concepts
- A single plant can be atypical
- Randomization reduces systematic placement bias
- A control provides a reference condition
- Replication improves confidence but does not fix a biased design
What to measure or observe
- Define the experimental unit before starting
- Randomize or balance positions when possible
- Measure the same traits with the same method
- Record excluded or failed samples transparently
Common mistakes
- Treating multiple leaves on one plant as multiple independent plants
- Comparing different cultivars as if genetics were controlled
- Changing several variables at once
Visuals this lesson still needs
- Replication diagram
- Randomized layout example
- Control-versus-treatment design
- Pseudoreplication warning graphic