Multiple Linear Regression
Full Form of MLR
What is MLR?
Multiple Linear Regression (MLR) is a statistical technique that models the linear relationship between one dependent variable and two or more independent variables. It extends simple linear regression by allowing multiple predictors to explain or forecast an outcome. In India, MLR is extensively used in academic research across disciplines like economics, agriculture, environmental science, and data analytics. For example, an economist might use MLR to study how GDP growth, inflation, and employment together affect consumer spending. The method is also employed in business for sales forecasting, in healthcare to predict disease risk factors, and in engineering for process optimization. Students encounter MLR in postgraduate statistics courses, MBA analytics programs, and data science bootcamps. It is a core topic for competitive exams such as UGC NET, GATE (Statistics or Data Science), and entrance tests for IIMs and ISI. Understanding MLR requires knowledge of matrix algebra, hypothesis testing, and diagnostic checks for multicollinearity and heteroscedasticity. With the rise of big data and AI, MLR remains a foundational tool for building predictive models in Indian industries and academia.
MLR का फुल फॉर्म
बहुविचर रेखीय प्रतिगमन
Example
In her study on air quality, Priya used MLR to analyze how traffic density, factory emissions, and temperature influence PM2.5 levels in Delhi.