This repository provides R functions to compute distorted M-quantiles, central regions, and depth functions for multivariate data, extending to multiple output regression settings.

This article demonstrates the preferred pattern for the application of logistic methods with an illustration of logistic regression applied to a data set in testing a research hypothesis.

Learn how to perform regression analysis of your data in Microsoft Excel, a statistical process that helps you understand the relationship ...

Spread the loveAn industry analysis report is a crucial document that provides detailed information about a specific industry’s performance, including its size, growth potential, trends, competitive ...

The data analysis used is multiple regression analysis using SPSS version 26.0 tools. The results of this research show that human resource competence has a positive effect on the performance of MSMEs ...

Finally, based on the resulting correlational pattern, we conducted a simultaneous multiple regression analysis to examine the relative contribution of participants’ study experience, previous ...

Discover the cost-effective and eco-friendly alternative to CEMS with Predictive Emission Monitoring Systems (PEMS). Learn how multiple regression and matrix algebra can accurately estimate industrial ...

Multiple correlation is used in multiple regression analysis to evaluate the fit of the model and the overall predictive power of the independent variables. What is multiple correlation?

Multiple linear regressions, statistical summaries, and t-tests are used for analysis and predictions. A study is also designed to compare this product to the competition.