03 idk
Experiment Pointers¶
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Always perform experiment with both trial & control samples
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Always get the raw data; processing should be done by analyst, not data providers
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Every data point should have central tendency & uncertainty associated
- Incorporate all potential uncertainty associated with collecting the data & use Uncertainty Propagation
- Preferably use robust summary statistics such as median and IQR, rather than mean & variance
- Every data point fed to model should be iid observation
Data Template¶
For Collection¶
Type | Category_ID | Subcategory_ID | Reading_ID | Value |
---|---|---|---|---|
Control | Product A | Sample 1 | 1 | x |
Control | Product A | Sample 1 | 2 | x |
Control | Product A | Sample 1 | 3 | x |
Control | Product A | Sample 2 | 1 | x |
Control | Product A | Sample 2 | 2 | x |
Control | Product A | Sample 2 | 3 | x |
Control | Product B | Sample 1 | 1 | x |
Control | Product B | Sample 1 | 2 | x |
Control | Product B | Sample 1 | 3 | x |
Control | Product B | Sample 2 | 1 | x |
Control | Product B | Sample 2 | 2 | x |
Control | Product B | Sample 2 | 3 | x |
Trial | … | … | … | … |
For Modelling¶
We cannot use the collection data directly for modelling as each row is not iid observation. Hence aggregation is required to obtain the central tendency & uncertainty for each iid observation.
Type | Category_ID | Subcategory_ID | Central Tendency (Median) | Uncertainty (IQR) |
---|---|---|---|---|
Control | Product A | Sample 1 | x | x |
Control | Product A | Sample 2 | x | x |
Control | Product B | Sample 1 | x | x |
Control | Product B | Sample 2 | x | x |
Trial | … | … | … | … |