https://github.com/razamehar/statistical-analysis-on-the-boston-housing-data
R-based statistical analysis of Boston Housing Data. Explored feature scales, computed descriptive stats, visualized data, and identified outliers (e.g., higher crime rates in specific areas). Examined variable relationships, calculated correlation coefficients, and presented findings via cross-classifications.
https://github.com/razamehar/statistical-analysis-on-the-boston-housing-data
boston-housing-dataset correlation-analysis cross-classification descriptive-statistics frequency-distribution outliers-detection r-programming statistical-analysis
Last synced: 3 months ago
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R-based statistical analysis of Boston Housing Data. Explored feature scales, computed descriptive stats, visualized data, and identified outliers (e.g., higher crime rates in specific areas). Examined variable relationships, calculated correlation coefficients, and presented findings via cross-classifications.
- Host: GitHub
- URL: https://github.com/razamehar/statistical-analysis-on-the-boston-housing-data
- Owner: razamehar
- License: mit
- Created: 2024-02-13T15:26:29.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-31T15:23:21.000Z (6 months ago)
- Last Synced: 2025-03-31T16:54:36.131Z (6 months ago)
- Topics: boston-housing-dataset, correlation-analysis, cross-classification, descriptive-statistics, frequency-distribution, outliers-detection, r-programming, statistical-analysis
- Homepage:
- Size: 853 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Statistical Analysis on the Boston Housing data
## Project Overview
This repository contains a comprehensive statistical analysis of the Boston Housing Data using the R programming language. The analysis delves into the scale of measurement for different features within the dataset, providing an understanding of the nature of the data. Descriptive statistics were also computed, offering insights into the central tendency and variability of the variables.Visualizations were employed to enhance the interpretation of the data, making patterns and trends more accessible. Outliers were identified and scrutinized, leading to observations such as the indication of higher crime rates in specific geographic areas. The analysis extends to exploring relationships between different variables within the dataset. Correlation coefficients were calculated to quantify these relationships, and the findings were thoroughly interpreted.
An examination of cross-classifications was conducted, shedding light on intricate associations between various aspects of the dataset. This work not only contributes to the understanding of the Boston Housing Data but also serves as a valuable resource for those interested in statistical analysis and data interpretation using the R programming language.
## Components of Analysis
- Scale of Measurement
- Descriptive Statistics
- Frequency Distribution
- Visual Exploration and Insights
- Outliers Detection and Contextual Understanding
- Relationship Identification using ScatterPlots
- Correlation Computation and Interpretation
- Cross-Classification## Prerequisites
- RStudio
- MASS or ISLR2 library## License
This project is licensed under the Raza Mehar License. See the [LICENSE.md](LICENSE.md) file for details.## Contact
For any questions or clarifications, please contact Raza Mehar at [raza.mehar@gmail.com].