Summary: This module introduces regression analysis and gives examples of regression analysis.

Regression analysis is any statistical method where the mean of one or more random variables is predicted based on other measured random variables [Wikipedia2006R]. There are two types of regression analysis, chosen according to whether the data approximate a straight line, when linear regression is used, or not, when non-linear regression is used.

A regression line is a line drawn through a scatterplot of two variables. The line is chosen so that it comes as close to the points as possible. Regression analysis, on the other hand, is more than curve fitting. It involves fitting a model with both deterministic and stochastic components. The deterministic component is called the predictor and the stochastic component is called the error term.

The simplest form of a regression model contains a dependent variable, also called the "Y-variable" and a single independent variable, also called the "X-variable".

Regression Analysis Graph |
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Examples of the regression of Y on X:

1. The dependence of the blood pressure Y on the age X of a person.

2. The dependence of the weight Y of certain animals on their daily ration of food X.

*References:*

Wikipedia2006R. "*Regression Analysis*,"
http://en.wikipedia.org/wiki/Regression_analysis, Last
Accessed on 20 February 2006

12manage. *Regression Analysis*. Accessed on February 20, 2006. At http://www.12manage.com/methods_regression_analysis.html

Author of Assignment 3: Lekulana Kolobe

Author of Assignment 1: Arnold Mwesigye