Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN: 9780133594140
Author: James Kurose, Keith Ross
Publisher: PEARSON
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**Title: Data Normalization in C++**

**Introduction:**
This educational module demonstrates how to create a C++ program that allows users to manually input employee salary data or read it from a text file. The program also illustrates how to normalize this data using different techniques.

**Employee Salary Data Table:**

| Employee  | Salary |
|-----------|--------|
| Employee A | 87000  |
| Employee B | 73600  |
| Employee C | 65000  |
| Employee D | 76000  |
| Employee E | 56200  |
| Employee F | 56900  |
| Employee G | 92000  |
| Employee H | 88000  |
| Employee I | 92300  |
| Employee J | 93560  |
| Employee K | 86541  |
| Employee L | 65320  |
| Employee M | 76022  |
| Employee N | 58000  |
| Employee O | 57000  |
| Employee P | 78360  |
| Employee Q | 59630  |
| Employee R | 69000  |
| Employee S | 87200  |
| Employee T | 76000  |
| Employee U | 63000  |

**Normalization Tasks:**

(a) *Min-Max Normalization:*
- The organization’s income range is between $50,000 to $96,000.
- To normalize to the range \([0, 1]\), calculate the normalized values for employees C, K, and Q using Min-Max normalization.

(b) *Z-Score Normalization:*
- Compute the z-score normalized salaries for employees D, G, and Q using their z-scores.

**Detailed Explanation:**

- **Min-Max Normalization Formula:**
  \[
  \text{Normalized Value} = \frac{(\text{Current Value} - \text{Min})}{(\text{Max} - \text{Min})}
  \]

- **Z-Score Normalization Formula:**
  \[
  \text{Z-Score} = \frac{(\text{Current Value} - \text{Mean})}{\text{Standard Deviation}}
  \]

**Conclusion:**
The exercise allows students to learn how to handle and normalize datasets programmatically, providing a foundation for more advanced data processing and analysis tasks.
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Transcribed Image Text:**Title: Data Normalization in C++** **Introduction:** This educational module demonstrates how to create a C++ program that allows users to manually input employee salary data or read it from a text file. The program also illustrates how to normalize this data using different techniques. **Employee Salary Data Table:** | Employee | Salary | |-----------|--------| | Employee A | 87000 | | Employee B | 73600 | | Employee C | 65000 | | Employee D | 76000 | | Employee E | 56200 | | Employee F | 56900 | | Employee G | 92000 | | Employee H | 88000 | | Employee I | 92300 | | Employee J | 93560 | | Employee K | 86541 | | Employee L | 65320 | | Employee M | 76022 | | Employee N | 58000 | | Employee O | 57000 | | Employee P | 78360 | | Employee Q | 59630 | | Employee R | 69000 | | Employee S | 87200 | | Employee T | 76000 | | Employee U | 63000 | **Normalization Tasks:** (a) *Min-Max Normalization:* - The organization’s income range is between $50,000 to $96,000. - To normalize to the range \([0, 1]\), calculate the normalized values for employees C, K, and Q using Min-Max normalization. (b) *Z-Score Normalization:* - Compute the z-score normalized salaries for employees D, G, and Q using their z-scores. **Detailed Explanation:** - **Min-Max Normalization Formula:** \[ \text{Normalized Value} = \frac{(\text{Current Value} - \text{Min})}{(\text{Max} - \text{Min})} \] - **Z-Score Normalization Formula:** \[ \text{Z-Score} = \frac{(\text{Current Value} - \text{Mean})}{\text{Standard Deviation}} \] **Conclusion:** The exercise allows students to learn how to handle and normalize datasets programmatically, providing a foundation for more advanced data processing and analysis tasks.
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