Skip to content Skip to navigation

Connexions

You are here: Home » Content » What is Linear Regression?

Navigation

Recently Viewed

This feature requires Javascript to be enabled.

What is Linear Regression?

Module by: Lekulana Kolobe. E-mail the author

User rating (How does the rating system work?)
Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

:
(0 ratings)

Summary: This module briefly introduces linear regression. It also includes an example and an exercise.

Linear regression is a method of estimating the conditional expected value of one variable, y, given the values of some other variable, x. The variable of interest, y, is called the dependent variable. The other variable, x, is called the independent variable. [Wikipedia2006L] The term linear is used because the relation of the dependent to the independent variables is assumed to be a linear function with two parameters. If this is not the case, then non-linear regression must be performed.

Example 1

A modeller may relate the weights of individuals to their heights using a linear regression model.

Before attempting to fit a linear model to observed data, a modeller should first determine whether or not there is a relationship between the variables of interest. A scatterplot can be a helpful tool in determining the strength of the relationship between two variables. A valuable numerical measure of association between two variables is the correlation coefficient, which is a value between -1 and 1 indicating the strength of the association of the observed data for the two variables.

Exercise 1

How can a linear regression be modelled?

Solution

A linear regression line has an equation of the form Y = a + bX, where X is the independent variable and Y is the dependent variable. The slope of the line is b, and a is the intercept: the value of Y when X = 0.

References:

Content actions

Give Feedback:

E-mail the module author | Rate module ( How does the rating system work?)

Rating system

Ratings

Ratings allow you to judge the quality of modules. If other users have ranked the module then its average rating is displayed below. Ratings are calculated on a scale from one star (Poor) to five stars (Excellent).

How to rate a module

Hover over the star that corresponds to the rating you wish to assign. Click on the star to add your rating. Your rating should be based on the quality of the content. You must have an account and be logged in to rate content.

(0 ratings)

Download:

Add module to:

My Favorites (?)

'My Favorites' is a special kind of lens which you can use to bookmark modules and collections directly in Connexions. 'My Favorites' can only be seen by you, and collections saved in 'My Favorites' can remember the last module you were on. You need a Connexions account to use 'My Favorites'.

| A lens (?)

Definition of a lens

Lenses

A lens is a custom view of Connexions content. You can think of it as a fancy kind of list that will let you see Connexions through the eyes of organizations and people you trust.

What is in a lens?

Lens makers point to Connexions materials (modules and collections), creating a guide that includes their own comments and descriptive tags about the content.

Who can create a lens?

Any individual Connexions member, a community, or a respected organization.

What are tags? tag icon

Tags are descriptors added by lens makers to help label content, attaching a vocabulary that is meaningful in the context of the lens.

| External bookmarks