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主にクロス表(分割表)分析をしようかなと思いはじめましたが、あまりクロス表の分析はできず。R言語の練習ブログになっています。

OECD Doctors' consultations data analysis 5 - Turkey has the most increased from 2007 to 2012.

f:id:cross_hyou:20210612193701j:plain

 Photo by Gwenn Klabbers on Unsplash  

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 This post is following of above post.

This time, let's see which country has the most increased doctors' consultation from 2007 to 2012.

f:id:cross_hyou:20210612193944p:plain

f:id:cross_hyou:20210612193959p:plain

We see TUR(Turkey) is the most incleasing country by net change.
Then, how about percent change?

f:id:cross_hyou:20210612194142p:plain

First, I make pct_chg.

f:id:cross_hyou:20210612194256p:plain

f:id:cross_hyou:20210612194309p:plain

For percent change, TUR(Turkey) is the top country too.

I suppose pct_chg is correlated to Y2007 value, the larger Y2007, the smaller pct_chg.

Let's check it with cor.test() function.

f:id:cross_hyou:20210612194529p:plain

correlation is -0.1558882, it is nagative. So Y2007 and pct_chg has negative correlation relationship, but p-value is 0.4024 and 96% confidence interval is -0.48 to 0.21. So, this negative correlation is not statistically significant.

Let's make a scatter plot for Y2007 and pct_chg.

f:id:cross_hyou:20210612195019p:plain

f:id:cross_hyou:20210612195031p:plain

I don't see linear relationship between Y2007 and pct_chg.
That's it . Thank you!

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