2012
DOI: 10.1590/s0001-37652012000400029
|View full text |Cite
|
Sign up to set email alerts
|

Use of the correlation coefficient in agricultural sciences: problems, pitfalls and how to deal with them

Abstract: This paper discusses a number of aspects concerning the analysis, interpretation and reporting of correlations in agricultural sciences. Various problems that one might encounter with these aspects are identified, and suggestions of how to overcome these problems are proposed. Some of the examples presented show how mistaken and even misleading the interpretation of correlation can be when one ignores simple rules of analysis.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
20
0
2

Year Published

2015
2015
2024
2024

Publication Types

Select...
8
1
1

Relationship

1
9

Authors

Journals

citations
Cited by 36 publications
(23 citation statements)
references
References 34 publications
(26 reference statements)
1
20
0
2
Order By: Relevance
“…If the data did not fit this distribution or outliers existed in datasets, the incorrect correlation coefficient could be calculated, causing misleading interpretations. For such skewed data including outliers, the nonparametric measure of association, named Spearman rank correlation, became a more appropriate alternative [52,53]. Before running the correlation analysis, we examined the distribution of all variables from the obtained data through a graphical method, normal quantile plot.…”
Section: Discussionmentioning
confidence: 99%
“…If the data did not fit this distribution or outliers existed in datasets, the incorrect correlation coefficient could be calculated, causing misleading interpretations. For such skewed data including outliers, the nonparametric measure of association, named Spearman rank correlation, became a more appropriate alternative [52,53]. Before running the correlation analysis, we examined the distribution of all variables from the obtained data through a graphical method, normal quantile plot.…”
Section: Discussionmentioning
confidence: 99%
“…Data of phytotoxicity of maize were correlated to the three foramsulfuron doses in order to asses Pearson's r correlation coefficient (Kozak et al, 2012). Pearson's r correlation coefficient was performed by using EXCEL ® function.…”
Section: Resultsmentioning
confidence: 99%
“…However, practice shows that far too often it is misinterpreted or misunderstood (Kozak et al, 2012). Path analysis partitions each individual rY value into a basic direct effect and 11 indirect effects.…”
Section: Paths Of Soil Respiration Causalitymentioning
confidence: 99%