Content deleted Content added
mNo edit summary |
m Open access bot: doi updated in citation with #oabot. |
||
Line 3:
[[Image:Okuns law quarterly differences.svg|300px|thumb|[[Okun's law]] in [[macroeconomics]] is an example of the simple linear regression. Here the dependent variable (GDP growth) is presumed to be in a linear relationship with the changes in the unemployment rate.]]
In [[statistics]], '''simple linear regression''' is a [[linear regression]] model with a single [[covariate|explanatory variable]].<ref>{{cite book |last=Seltman |first=Howard J. |date=2008-09-08 |title=Experimental Design and Analysis |url=http://www.stat.cmu.edu/~hseltman/309/Book/Book.pdf |page=227}}</ref><ref name=":0">{{cite web |url=http://ci.columbia.edu/ci/premba_test/c0331/s7/s7_6.html |title=Statistical Sampling and Regression: Simple Linear Regression |publisher=Columbia University |access-date=2016-10-17 |quote=When one independent variable is used in a regression, it is called a simple regression;(...)}}</ref><ref>{{cite book |last=Lane |first=David M. |title=Introduction to Statistics |url=http://onlinestatbook.com/Online_Statistics_Education.pdf |page=462}}</ref><ref>{{Cite journal|last1=Zou KH|last2=Tuncali K|last3=Silverman SG|date=2003|title=Correlation and simple linear regression.|journal=Radiology|language=English|volume=227|issue=3|pages=617–22|issn=0033-8419|oclc=110941167|doi=10.1148/radiol.2273011499|pmid=12773666|url=https://repositorio.unal.edu.co/handle/unal/81200 }}</ref><ref>{{Cite journal|last1=Altman|first1=Naomi|last2=Krzywinski|first2=Martin|date=2015|title=Simple linear regression|journal=Nature Methods|language=English|volume=12|issue=11|pages=999–1000|issn=1548-7091|oclc=5912005539|doi=10.1038/nmeth.3627|pmid=26824102|s2cid=261269711 |doi-access=free}}</ref> That is, it concerns two-dimensional sample points with [[dependent and independent variables|one independent variable and one dependent variable]] (conventionally, the ''x'' and ''y'' coordinates in a [[Cartesian coordinate system]]) and finds a linear function (a non-vertical [[straight line]]) that, as accurately as possible, predicts the dependent variable values as a function of the independent variable.
The adjective ''simple'' refers to the fact that the outcome variable is related to a single predictor.
|