Line of Best Fit in Statistics
In statistics, the line of best fit, also known as the trend line, is a straight line that best represents the data points on a scatter plot. This line attempts to show the relationship between two variables by minimizing the distances between the points and the line itself, specifically the vertical distances. The process of finding this line involves a method called linear regression, where the goal is to minimize the sum of the squares of these vertical distances, a technique often referred to as the “least squares” method.
Line of Best Fit
Line of Best Fit: A Line of best fit is a fundamental concept of statistics used to analyze the relationship between two variables. It helps predict the values of one variable based on the values of another variable(given).
Line of best fit is a straight line drawn through a scatter plot of data points that best represent their distribution by minimizing the distances between the line and these points. It results from regression analysis and serves to illustrate the relationship among the data. This line is also a predictive tool, useful for forecasting trends, such as market indicators and price movements.
In this article, we will learn about the Line of Best Fit, how to calculate the line of best fit, solved examples, and other in detail in this article.
Table of Content
- What Is a Line of Best Fit?
- Line of Best Fit in Regression
- Line of Best Fit in Statistics
- Line of Best Fit Formula
- How to Calculate the Line of Best Fit?
- Is a Line of Best Fit Always Straight?
- Where Line of Best Fit is Used?
- Line of Best Fit Examples
- Line of Best Fit – Practice Questions