This example calculates the Pearson correlation coefficient (r), by measuring the linear relationship between two arrays. The use of means and then the accumulators, shows how covariance and variance combine into (r), with results from -1 to +1. Implemented in Python, MATLAB, and JavaScript.
Super Store Sales and Profit Data set
Modeling the Closing Prices of Alior Bank and ING with an Analysis of the Joint Distribution of Returns
Employee Turnover Prediction using machine learning, focusing on data preprocessing, Visualization, Model development, Streamlit, Flask and deploying a dashboard for HR analytics.
HealthAnalytics-SAS: Leveraging SAS Programming to Uncover Health Trends, Correlations, and Predictive Insights from Comprehensive Health Data Analysis.
Terro's Real Estate analyzes Boston house prices with a 506-house dataset. Initial models with LSTAT set baselines; subsequent models refine predictions, achieving an impressive adjusted R-squared of 0.6887. Insights guide precise pricing, showcasing Terro's commitment to industry standards. Addressing challenges enriches the project's narrative.
Exploring the integration of Vedic Hindu lunisolar calendar insights into time series analysis for enhancing weather prediction.
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