Review of Regression and Different Regression Models
Learn to identify and apply different regression models including linear, polynomial, and logistic regression. Understand how these models help predict outcomes and analyze relationships between variables in data, enhancing your ability to interpret and visualize data patterns effectively.
We'll cover the following...
Regression models
Regression models are used to perform regression analysis. Regression analysis helps us to determine the relationships between two or more variables and infer any underlying patterns among them. We use it primarily for the following purposes:
- To predict a variable based on one or more variables.
- To analyze the influence of one (or more) variables on another variable.
Let’s say we want to analyze the factors affecting the chances of a particular student getting a scholarship. Certain factors may influence the student’s acceptance chances, such as their grades, publications, a well-written statement of purpose (SOP), and so on. Every factor can positively or negatively influence their chances of getting a scholarship.
Likewise, let’s say we want to predict the resell price of a car based on certain factors such as mileage, accident history, condition, model, and so on. Every factor may have a positive or negative impact on the final resell price. For example, the latest model of a car may increase the resell price, whereas if it has ...