A B + I + + Treatment Combination (1) a b ab I 18.2 27.2 15.9 41.0 Replicate II 18.9 24.0 14.5 43.9 III IV 12.9 14.4 22.4 22.5 15.1 14.2 36.3 39.9

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  1. A router is used to cut locating notches on a printed circuit board. The vibration level at the surface of the board as it is cut is considered to be a major source of dimensional variation in the notches. Two factors are thought to influence vibration: bit size (A) and cutting speed (B). Two bit sizes (1/16 and 1/8 inch) and two speeds (40 and 90 rpm) are selected, and four boards are cut at each set of conditions shown below. The response variable is vibration measured as a resultant vector of three accelerometers (x, y, and z) on each test circuit board.

(a) Analyze this experiment assuming that each one of the four replicates represent a block.

(b) 

 

### Table: Treatment Combinations and Replicate Measurements

This table presents the results of an experiment involving different treatment combinations and their corresponding replicate measurements.

| A   | B   | Treatment Combination | Replicate I | Replicate II | Replicate III | Replicate IV |
|-----|-----|-----------------------|-------------|--------------|---------------|--------------|
| -   | -   | (1)                   | 18.2        | 18.9         | 12.9          | 14.4         |
| +   | -   | a                     | 27.2        | 24.0         | 22.4          | 22.5         |
| -   | +   | b                     | 15.9        | 14.5         | 15.1          | 14.2         |
| +   | +   | ab                    | 41.0        | 43.9         | 36.3          | 39.9         |

**Explanation:**

- **Columns A and B**: Indicate the presence (+) or absence (-) of two factors, A and B, in the treatment combinations.
  
- **Treatment Combinations**:
  - (1): Neither factor A nor B is present (-, -).
  - \(a\): Only factor A is present (+, -).
  - \(b\): Only factor B is present (-, +).
  - \(ab\): Both factors A and B are present (+, +).

- **Replicates I to IV**: These columns contain the numerical data representing the results of four replicate measurements for each treatment combination. The values can be used to assess the consistency and reliability of the experimental outcomes across different experimental runs.
Transcribed Image Text:### Table: Treatment Combinations and Replicate Measurements This table presents the results of an experiment involving different treatment combinations and their corresponding replicate measurements. | A | B | Treatment Combination | Replicate I | Replicate II | Replicate III | Replicate IV | |-----|-----|-----------------------|-------------|--------------|---------------|--------------| | - | - | (1) | 18.2 | 18.9 | 12.9 | 14.4 | | + | - | a | 27.2 | 24.0 | 22.4 | 22.5 | | - | + | b | 15.9 | 14.5 | 15.1 | 14.2 | | + | + | ab | 41.0 | 43.9 | 36.3 | 39.9 | **Explanation:** - **Columns A and B**: Indicate the presence (+) or absence (-) of two factors, A and B, in the treatment combinations. - **Treatment Combinations**: - (1): Neither factor A nor B is present (-, -). - \(a\): Only factor A is present (+, -). - \(b\): Only factor B is present (-, +). - \(ab\): Both factors A and B are present (+, +). - **Replicates I to IV**: These columns contain the numerical data representing the results of four replicate measurements for each treatment combination. The values can be used to assess the consistency and reliability of the experimental outcomes across different experimental runs.
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