This project performs rigorous statistical analysis on various datasets to validate real-world claims. It employs descriptive statistics, probability distributions, and hypothesis testing frameworks.
- Algorithm Performance Analysis: Histogram analysis of execution times to determine distribution shape.
- Descriptive Statistics: Skewness and Coefficient of Variation (CV) analysis for production cost vs. profit volatility.
- Probability Modeling: Application of Normal Distribution concepts to web server response times and download speeds.
- Hypothesis Testing:
- Z-Test: Validating system optimization claims (n=50).
- T-Test: Analyzing student study habits against academic claims (n=15).
- Microsoft Excel: Advanced formulas (
NORM.DIST,T.DIST,Z.TEST), Pivot Tables, and Data Visualization. - Statistical Methods: Confidence Intervals, P-Value determination, and Outlier detection.
This project was created for educational purposes as part of the Probability & Statistics curriculum.