Distribution Testing Using K-S Test for Multiple Distributions
- Login to Download
- 1 Credits
Resource Overview
This program analyzes dataset compliance with various distributions (normal, exponential, or double exponential) and performs goodness-of-fit testing using the Kolmogorov-Smirnov (K-S) test method, including implementation of distribution parameter estimation and test statistic calculation algorithms.
Detailed Documentation
This program is designed to perform distribution testing on datasets to determine their compliance with normal, exponential, or double exponential distributions, utilizing the Kolmogorov-Smirnov (K-S) test for statistical validation. The implementation includes maximum likelihood estimation for distribution parameters and calculates the K-S test statistic through empirical cumulative distribution function comparison. Additionally, the program generates multiple visualization charts (probability plots, Q-Q plots) and provides comprehensive statistical metrics (p-values, test statistics, confidence intervals) to facilitate better understanding of distribution characteristics. Through these analytical tools and implemented algorithms, users can gain accurate insights into data behavior for improved decision-making in statistical applications.
- Login to Download
- 1 Credits