statistical-analysis

A Python project for statistical analysis and SAT data processing.

Features

• Data cleaning and preprocessing for tabular and time series data
• Hypothesis testing (Mann-Whitney U, Chi-Square, Kruskal-Wallis)
• Linear regression modeling with multicollinearity checks (VIF)
• Time series analysis and forecasting (ARIMA, SARIMA)
• Automated result and plot generation
• Modular, extensible codebase

Features

• Data import and export
• Statistical computations (mean, median, standard deviation, correlation, etc.)
• Visualization tools (histograms, scatter plots, box plots)
• Modular and extensible design

Types of Analysis

• Hypothesis Testing: Explore relationships and differences in student performance data.
• Linear Regression: Identify and quantify predictors of student final scores.
• Time Series Analysis: Decompose, model, and forecast stock prices.

Installation

git clone https://github.com/yourusername/sat-private.git
cd sat-private
pip install -r requirements.txt

Usage

1. Place your datasets in the Datasets/ directory:
   • Students_Grading_Dataset.csv
   • apple_only.csv
2. Run the main script:

   python main.py

3. Results and plots will be saved in the output/ directory.

Project Structure

sat-private/
├── Data_Cleaning/
│   └── preprocessing.py
├── Regression/
│   └── linear_regression.py
├── Hypothesis/
│   └── hypothesis_testing.py
├── Time_Series/
│   └── time_series_analysis.py
├── Datasets/
│   ├── Students_Grading_Dataset.csv
│   └── apple_only.csv
├── output/
│   └── [results and plots]
├── main.py
└── README.md