Correlation analysis

BHornink

1 min read

·

May 18, 2023

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*creating a dataframe*;
data correlation
        input tree dbh heigh production; 
        label   /*assigning labels to the data headers*/ 
        tree = "Tree" 
        dbh = "DBH (m)" 
        height = "Height (m)" 
        production = "Production(kg)";
datalines; 
1 0.20 5.06 2.32 
2 0.21 6.24 2.23
3 0.40 7.16 4.61
4 0.24 5.47 3.16
5 0.19 5.50 2.13
6 0.10 5.39 2.00 
7 0.15 5.84 2.46 
8 0.25 5.40 2.86 
9 0.20 5.43 2.49
10 0.13 7.25 1.58
11 0.16 6.69 1.78 
12 0.14 5.41 1.74
13 0.13 5.69 1.60
14 0.24 22.45 2.43
15 0.07 6.33 1.62
16 0.43 7.25 4.96 
17 0.19 5.38 2.18 
18 0.25 5.59 2.62 
19 0.17 5.38 2.63 
20 0.33 6.99 3.33 
21 0.15 6.05 1.76 
22 0.22 6.85 3.22 
23 0.32 6.41 3.47 
24 0.27 5.39 2.95 
25 0.30 8.99 2.99 
26 0.26 6.40 2.84 
27 0.35 10.54 4.15 
28 0.24 5.58 3.23 
29 0.20 5.30 2.63 
30 0.50 8.55 5.04
;

*running the dataframe*;
proc print data = correlation label noobs;     
/*noobs: remove the observations column from the dataframe*/
title: "..:: Production of essential oils  (kg) ::.."; 
run; 

*person x spearman correlation*;
proc corr data = correlation pearson spearman nosimple;  
/* pearson: brings the Pearson statistics;
spearman: the Spearman statistic;
nosimples: removes the basic statistics of mean and standard deviation*/
        var  production; 
        with dbh height; 
run; 

*pearson x spearman correlation with histomgram*;
proc corr data = correlation plots=matrix(histogram) spearman nosimple;
        var  production; 
        with dbh height; 
run;