MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -Example: we can say that age and height can be described using a linear regression model. Since a person’s height increases as age increases, they have a linear relationship. Regression models are commonly used as statistical proof of claims regarding everyday facts.

Detailed explanation-2: -Some real-world examples for regression analysis include predicting the price of a house given house features, predicting the impact of SAT/GRE scores on college admissions, predicting the sales based on input parameters, predicting the weather, etc.

Detailed explanation-3: -For example, it can be used to predict the relationship between reckless driving and the total number of road accidents caused by a driver, or, to use a business example, the effect on sales and spending a certain amount of money on advertising. Regression is one of the most common models of machine learning.

Detailed explanation-4: -Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable’s value is called the independent variable.