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https://github.com/farhad-here/height-distribution-analysis

Statistical comparison of height distributions in two groups using mean, standard deviation, and boxplots.
https://github.com/farhad-here/height-distribution-analysis

coefficient-of-variation data-analysis interquartile-ranges matplotlib mean numpy python scipy standard-deviation variance

Last synced: 7 months ago
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Statistical comparison of height distributions in two groups using mean, standard deviation, and boxplots.

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# Height Distribution Analysis

This project analyzes the **height distribution** of two synthetic groups (A and B) based on normal distributions.

---

## 📊 Problem Statement

- **Group A:** Heights follow a normal distribution with a mean of 175 cm and a standard deviation of 5 cm.
- **Group B:** Heights follow a normal distribution with a mean of 170 cm and a standard deviation of 15 cm.

We randomly generate 100 height values for each group and analyze:

- Mean and standard deviation
- Boxplots to visualize spread and outliers
- Which group has greater variability?

---

## 📎 Objectives

- Generate height data for each group
- Calculate:
- Mean
- Standard Deviation
- variance
- Range
- Interquartile Range
- Coefficient of Variation
- Plot boxplots
- Interpret the results

---
# Group_A:
- Mean: 174.48
- Standard Deviation: 4.52
- variance: 20.413054867346467
- Range: 43.042959152030306
- Interquartile Range:
5.034288612542554
- Coefficient of Variation:
0.00025894434958140586
# Group_B:
- Mean: 170.33
- Standard Deviation: 14.23
- variance: 202.58767172028197
- Range: 69.58410572832992
- Interquartile Range:
20.15746456230474
- Coefficient of Variation:
0.0008356101587277632

# 🧰 Requirements
- Python 3.x

- NumPy

- Matplotlib
- scipy
Install required libraries:

```bash
pip install numpy matplotlib scipy
```

🧑‍💻 Author
Made with ❤️ by FarhadGhaherdoost