Difference between revisions of "Worksheets/Week6"
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The 16 experiments from a full factorial, 2^4 = 16, were randomly run, and the yields, y, the outcome variable were given in standard order: <tt>[60, 59, 63, 61, 69, 61, 94, 93, 56, 63, 70, 65, 44, 45, 78, 77]</tt> | The 16 experiments from a full factorial, 2^4 = 16, were randomly run, and the yields, y, the outcome variable were given in standard order: <tt>[60, 59, 63, 61, 69, 61, 94, 93, 56, 63, 70, 65, 44, 45, 78, 77]</tt> | ||
<html><div data-datacamp-exercise data-lang="r" data-height=" | <html><div data-datacamp-exercise data-lang="r" data-height="800px"> | ||
<code data-type="sample-code"> | <code data-type="sample-code"> | ||
Revision as of 09:10, 17 October 2019
Part 1
Case study: Achieve a stability value of 50 days or more, for a new product. We had a full factorial set of experiments in 3 factors:
| Factor name | Description | Low value | High value | Type of factor |
|---|---|---|---|---|
| A | Enzyme strength | 20% | 30% | Numeric factor |
| B | Feed concentration | 75% | 85% | Numeric |
| C | Mixer type | R | W | Categorical |
We will show what we loose out if we pretend we only did half the experiments. In other words, we actually have 8 experiments, but we will see what happens if we only use 4 of them.
Part 2
Data from a bioreactor experiment is available, were we were investigating four factors:
| Factor name | Description | Low value | High value | Type of factor |
|---|---|---|---|---|
| A | Feed rate | 5 g/min | 8 g/min | Numeric factor |
| B | Initial inoculant amount | 300 g | 400 g | Numeric |
| C | Feed substrate concentration | 40 g/L | 60 g/L | Numeric |
| D | Dissolved oxygen set-point | 4 mg/L | 5 mg/L | Numeric |
The 16 experiments from a full factorial, 2^4 = 16, were randomly run, and the yields, y, the outcome variable were given in standard order: [60, 59, 63, 61, 69, 61, 94, 93, 56, 63, 70, 65, 44, 45, 78, 77]