a. Compute the first principal component score for observation 1. (Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.) PC1,1 b. Compute the second principal component score for observation 2. (Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.) PC22 c. Compute the third principal component score for observation 3. (Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.) PC33
a. Compute the first principal component score for observation 1. (Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.) PC1,1 b. Compute the second principal component score for observation 2. (Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.) PC22 c. Compute the third principal component score for observation 3. (Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.) PC33
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
![**Principal Component Analysis Exercise**
1. **Compute the First Principal Component Score for Observation 1**
- *Instruction*: Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.
- Formula Box: \(PC_{1,1}\) [Input box]
2. **Compute the Second Principal Component Score for Observation 2**
- *Instruction*: Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.
- Formula Box: \(PC_{2,2}\) [Input box]
3. **Compute the Third Principal Component Score for Observation 3**
- *Instruction*: Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.
- Formula Box: [Input box]](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F80f5a0b5-fa3f-4609-a3a3-be6affb5f07a%2F32af809a-a31a-411e-a3d3-ceb7ab77e585%2Fjsrats_processed.png&w=3840&q=75)
Transcribed Image Text:**Principal Component Analysis Exercise**
1. **Compute the First Principal Component Score for Observation 1**
- *Instruction*: Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.
- Formula Box: \(PC_{1,1}\) [Input box]
2. **Compute the Second Principal Component Score for Observation 2**
- *Instruction*: Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.
- Formula Box: \(PC_{2,2}\) [Input box]
3. **Compute the Third Principal Component Score for Observation 3**
- *Instruction*: Round intermediate calculations to at least 4 decimal places and your final answer to 4 decimal places. Negative value should be indicated by a minus sign.
- Formula Box: [Input box]

Transcribed Image Text:The following table displays the weights for computing the principal components and the standardized data (z-scores) for three observations.
| Weight | \(PC_1\) | \(PC_2\) | \(PC_3\) |
|--------|--------|--------|--------|
| \(x_1\) | -0.65 | 0.69 | 0.60 |
| \(x_2\) | -0.70 | 0.12 | -0.84 |
| \(x_3\) | 0.72 | 0.86 | -0.33 |
---
| | \(Z_1\) | \(Z_2\) | \(Z_3\) |
|--------|--------|--------|--------|
| Observation 1 | 0.82 | 0.40 | -0.31 |
| Observation 2 | 2.81 | 2.61 | -1.22 |
| Observation 3 | -0.89 | -1.12 | 1.39 |
The first table contains the weights assigned to each variable (\(x_1, x_2, x_3\)) for the computation of the principal components (\(PC_1, PC_2, PC_3\)).
The second table shows the standardized data or z-scores (\(Z_1, Z_2, Z_3\)) for three observations. Each cell represents the z-score of a particular observation for the corresponding principal component.
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