TY - JOUR
T1 - Cate-Nelson analysis for bivariate data using R-project
AU - Mangiafico, Salvatore S.
PY - 2013/10
Y1 - 2013/10
N2 - In Extension, it is helpful to be able to analyze data in simple and innovative ways that produce easily interpretable results. Cate-Nelson analysis is a simple way to divide bivariate data into two populations to emphasize the relationship between the x variable and y variable. While a Cate-Nelson analysis could be performed by manually calculating iterative Sums of Squares to determine the best fit, this process could be partially automated with the included SAS code. Alternatively, the included R-project code automatically completes the analysis, outputs the relevant statistics, and produces the relevant plots.
AB - In Extension, it is helpful to be able to analyze data in simple and innovative ways that produce easily interpretable results. Cate-Nelson analysis is a simple way to divide bivariate data into two populations to emphasize the relationship between the x variable and y variable. While a Cate-Nelson analysis could be performed by manually calculating iterative Sums of Squares to determine the best fit, this process could be partially automated with the included SAS code. Alternatively, the included R-project code automatically completes the analysis, outputs the relevant statistics, and produces the relevant plots.
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M3 - Article
AN - SCOPUS:84887131619
SN - 1077-5315
VL - 51
JO - Journal of Extension
JF - Journal of Extension
IS - 5
M1 - 5TOT1
ER -