Question 1131511


Regression and correlation analysis procedures are used to study the relationships between variables.
  
{{{Regression}}} is used to {{{predict}}} the {{{value}}} of {{{one}}}{{{ variable}}} based on the {{{value }}}of a {{{different}}}{{{ variable}}}. 
 
{{{Correlation}}} is a measure of the strength of a relationship between variables.  The variables are data which are measured and/or counted in an experiment. 

{{{Regression}}} {{{analysis }}}is used to {{{understand}}}, {{{model}}}, {{{predict}}}, and/or {{{explain}}} complex phenomena. 

It helps you answer why questions like "{{{Why}}} are there places in the United States with test scores that are consistently above the national average?" or "{{{Why}}} are there areas of the city with such high rates of residential burglary?" 
You might use regression analysis to explain childhood obesity, for example, using a set of related variables such as income, education, and accessibility to healthy food.

Typically, regression analysis helps you answer these why questions so that you can do something about them. If, for example, you discover that childhood obesity is lower in schools that serve fresh fruits and vegetables at lunch, you can use that information to guide policy and make decisions about school lunch programs. Likewise, knowing the variables that help explain high crime rates can allow you to make predictions about future crime so that prevention resources can be allocated more effectively.


so, always look for:

do you need to {{{predict}}} the {{{value}}} of {{{one}}}{{{ variable}}} based on the {{{value }}}of a {{{different}}}{{{ variable}}} based on given data {{{analysis }}}