Multiple Linear Regression

Multiple Linear Regression (MLR) is a statistical technique used to model the relationship between a dependent variable and two or more independent variables. It extends simple linear regression by allowing multiple predictors, making it useful for more complex data where a single variable does not explain the outcome adequately. Formula for Multiple Linear Regression The general formula for a multiple linear regression model is: 𝑌 = 𝛽0 + 𝛽1𝑋1 + 𝛽2𝑋2 + ⋯ +𝛽𝑛𝑋𝑛 + 𝜖 Where:

Exploring Air Quality in New York: A Predictive Analysis of Ozone Levels Using Environmental Factors

For this analysis, we will explore the airquality dataset, which provides daily air quality measurements in New York from May to September 1973. The dataset includes variables such as Ozone, Solar.R (solar radiation), Wind, Temp (temperature), and the month and day of the observation. Our objective is to analyze the relationships between air quality and weather-related factors, focusing on predicting the levels of Ozone, a key indicator of air pollution.