Multivariate Analysis for Data Science

Multivariate analysis is a type of statistical analysis, which consists of more than two dependent variables which results in single outcome. Many real world problems are examples of multivariate equations because whatever happens in the world is due to multiple reasons. Multivariate analysis is very important as it enables to understand the relationship between multiple variables and forecast and predict the behavior of variables based on observations. Multivariate techniques are used to analyze dataset. It also measures latent variables by building structural equation model. It also helps in reduction and simplification of data without losing its important details. It helps in statistical inference of multiple independent as well as dependent variables.

Autorentext

Dr. Varsha D. Jadhav is working at Vishwakarma Institute of Information Technology, Pune, Maharashtra, India. She Holds a PhD degree in Computer Engineering with specialization in Data Science. She is having 20 years of experience. She has received 3 best paper awards. She is active member of Society for Data Science, India.