Research:Mother Feelbright's Busy Bees
I have the following research on shaping effects:
|Dollops||239 bonus||311 bonus|
|1||Professional honey handler||Professional honey handler|
|2||Professional honey handler||Professional honey handler|
|3||Professional honey handler||Professional honey handler|
|4||Professional honey handler||Professional honey handler|
|5||Ease||Professional honey handler|
|6||Ease||Professional honey handler|
|11||Slight difficulty||Relative ease|
|19||Severe difficulty||Severe difficulty|
|20||Severe difficulty||Severe difficulty|
From this I've deduced:
- There's a 'pivot point', which seems to be 'sqrt(bonus) - 5.5'
- Dollops <= floor(pivot * 0.5) dollops is 'professional honey handler'
- floor(pivot * 0.5) < dollops <= floor(pivot * 0.75) is 'ease'
- floor(pivot * 0.75) < dollops <= floor(pivot * 0.95) is 'relative ease'
- floor(pivot * 0.95) < dollops <= floor(pivot * 1.05) results in no adverb.
- floor(pivot * 1.05) < dollops <= floor(pivot * 1.25) is 'slight difficulty'
- floor(pivot * 1.25) < dollops <= floor(pivot * 1.55) is 'difficulty'
- floor(pivot * 1.55) < dollops is 'severe difficulty'
At the moment I only have two data sets; the categorizations seem to fit pretty well, but I think more research might be needed to confirm the formula for the pivot point.
It's also not currently clear what the relationship between the categorizations and the bonus/penalty to throwing that results from them is - so more research is needed there. --Chat 22:49, 3 September 2009 (UTC)