PointBiserial Correlation  Python for Integrated Circuits   An Online Book  

Python for Integrated Circuits http://www.globalsino.com/ICs/  


Chapter/Index: Introduction  A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  Appendix  
================================================================================= Pointbiserial correlation is a statistical measure used to assess the strength and direction of the relationship between a binary (dichotomous) variable and a continuous variable. It is a specific type of correlation coefficient that quantifies the association between two variables when one of them is binary (taking on only two values, typically 0 and 1) and the other is continuous (taking on a range of values). The pointbiserial correlation coefficient is denoted by rpb or simply r, and its value can range from 1 to 1. The sign of the coefficient indicates the direction of the relationship:
The pointbiserial correlation coefficient is computed using the following formula:  [3917] Where:
Pointbiserial correlation is often used in situations where you want to examine the relationship between a binary independent variable (e.g., gender) and a continuous dependent variable (e.g., test scores). It helps you determine if there's a significant association between the two variables and quantify the strength and direction of that association. ============================================ The script below loads data from multiple folders, calculates pointbiserial correlation coefficients between binary and continuous variables, identifies the best correlations for each folder, and calculates overall correlations for each folder, providing a summary of the relationships between variables within and across different folders. Code: ============================================


=================================================================================  

