[R] how to proof the trend of two columns of data?

[vod vos]

as far as I know,  ?kruskal.test will show us the differences between three or more groups. But it could show the trend. 




---- On 星期一, 09 一月 2017 10:12:14 -0800 David L Carlson <dcarlson at tamu.edu> wrote ----




The list does not assist with homework problems. If this is not a class assignment, you should be more specific about what you have tried and provide a reproducible example (a sample of the real data or some made-up data that has the same columns and data types). In the meantime you could also try the following R command: 

 

> ?kruskal.test 

 

------------------------------------- 

David L Carlson 

Department of Anthropology 

Texas A&M University 

College Station, TX 77840-4352 



-----Original Message----- 

From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Rui Barradas 

Sent: Monday, January 9, 2017 11:28 AM 

To: vod vos; r-help 

Subject: Re: [R] how to proof the trend of two columns of data? 



Hello, 



Inline. 



Em 09-01-2017 14:55, vod vos escreveu: 

> Hello everyone, 

> 

> 

> 

> If there are two columns, one is age (numeric, cut to several groups), the other is hair color type(factor: yellow, black, white). 

> 

> 

> 

> If the age column is not normal distributed 



If you use ?lm, it's the residuals that should be normally distributed, 

not age. 

You can also use ?glm with a binomial link, in which case you should 

recode type as white/not white. 



Hope this helps, 



Rui Barradas 



, which statistic method should use to prove the trend relationship 

between them, for example, the older has more probability of white hair 

type? Are there any existed R package to figure out this situation? 

> 

> 

> 

> Thank you. 

> 

> 

> 

> 

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> 

> ______________________________________________ 

> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see 

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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html 

> and provide commented, minimal, self-contained, reproducible code. 

> 



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______________________________________________ 

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