Linear regression is a statistical technique used to describe a variable as a function of one or more predictor variables. Learn more with videos and examples.
Linear regression is an analytics procedure that can generate predictions by using an easily interpreted mathematical formula.
For example, if the linear model is E(y) = 1.8 – 2.35X1 + X2, then –2.35 indicates a 2.35 unit decrease in the mean response with a one-unit increase in X1, given X2 is held constant. If the model is E(y) = 1.1 + 1.5X12 + X2, the coefficient of X12 indicates a 1.5 ...
Each specific approach can be applied to different tasks or data analysis objectives. For example, HLM -- also called multilevel modeling -- is a type of linear model intended to handle nested or hierarchical data structures, while ridge regression can be used when there's a high correlation ...
To Reference this Page:Statistics Solutions. (2025). What is Linear Regression . Retrieved fromhere. Related Pages: Assumptions of a Linear Regression Take the course:Linear Regression Step Boldly to Completing your Research If you’re like others, you’ve invested a lot of time and money devel...
Linear analysis is one type of regression analysis. For example, the equation for a line is y = a + bX. Y is the dependent variable in the formula, which one tries to predict what will be the future value if X, an independent variable, changes by a certain value. The “a” in ...
Simple linear regression has two parameters: an intercept (c), which indicates the value that the label is when the feature is set to zero; and a slope (m), which indicates how much the label will increase for each one-point increase in the feature....
What is Regression?: Regression is a statistical technique used to analyze the data by maintaining a relation between the dependent and independent variables.
Linear regression relates two variables with a straight line; nonlinear regression relates the variables using a curve. Example of Nonlinear Regression One example of how nonlinear regression can be used is to predict population growth over time.1A scatterplot of changing population data over time sho...
Example: Let’s assume thereis a telecom network called Neo. Its delivery manager wants to find out if there’s a relationship between the monthly charges of a customer and the tenure of the customer. So, he collects all customer data and implements linear regression by taking monthly charge...