MTH-416, REGRESSION ANALYSIS Lecture 1: Chapter1-Regression-Introduction

• School: Indian Institute of Technology - IIT Kanpur
• Department: Mathematics
• Course: MTH-416, REGRESSION ANALYSIS
• Professor: All

Document Summary

Linear models play a central part in modern statistical methods. On the one hand, these models can approximate a large amount of metric data structures in their entire range of definition or at least piecewise. Suppose the outcome of any process is denoted by a random variable y , called as dependent (or study) variable, depends on k independent (or explanatory) variables denoted by. X suppose the behaviour of y can be explained by a relationship given by. X f x x. 2 where f is some well-defined function and. Are the parameters which characterize the role and. The term reflects the stochastic nature of the relationship k k. X indicates that such a relationship is not exact in nature. When between y and then the relationship is called the mathematical model otherwise the statistical model. The term model is broadly used to represent any phenomenon in a mathematical framework.