R Notebook

creamos el ambiente

Cargar los datos

data_profe_3_1 <- 
  tibble(words = numeric(),
         precision = numeric(), 
         pert = numeric())

for (i in files_3_1$nombres_3){
  data_3_1 = read_excel(i, 
                      col_names = FALSE) %>% 
    select(3,5,7) %>% 
    rename(words = "...3",
           precision = "...5",
           pert = "...7") %>% 
    mutate(metodo = i,
           metodo = str_remove(metodo, 
                               ".xlsx"),
           metodo = str_remove(metodo, 
                               "data/")) 
  
  data_profe_3_1 <- 
    bind_rows(data_profe_3_1,
              data_3_1)
}
  

data_profe_3_2 <- 
  tibble(words = numeric(),
         precision = numeric(), 
         pert = numeric())

for (i in files_3_2$nombres_3){
  data_3_2 = read_excel(i, 
                      col_names = FALSE) %>% 
    select(1,3,5) %>% 
    rename(words = "...1",
           precision = "...3",
           pert = "...5") %>% 
    mutate(metodo = i,
           metodo = str_remove(metodo, 
                               ".xlsx"),
           metodo = str_remove(metodo, 
                               "data/")) 
  
  data_profe_3_2 <- 
    bind_rows(data_profe_3_2,
              data_3_2)
}

Unimos los dos archivos

Analizamos los datos

Como los datos no tienen una distribución normal entonces se realiza la prueba de Kruskal Wallis para determinar si hay diferencias entre medianas.

kruskal.test(metodo ~ precision, 
             data_profe_3 )

    Kruskal-Wallis rank sum test

data:  metodo by precision
Kruskal-Wallis chi-squared = 1028.9,
df = 440, p-value < 2.2e-16

Como el p-valor es menor a 0.05 se rechaza la Ho. Por lo tanto, hay diferencias entre las medianas.

Ahora es necesario saber entre cuáles variables hay diferencias y para esto se utiliza un análisis pos hoc de comparaciones múltiples Pairwise Wilcox.

pairwise.wilcox.test(data_profe_3$precision,
                     data_profe_3$metodo,
                     p.adjust.method = "BH")

    Pairwise comparisons using Wilcoxon rank sum test with continuity correction 

data:  data_profe_3$precision and data_profe_3$metodo 

                                    1_ENmatResPreRec_Hyb_vsm_UMBAQEtype
2_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.77654                            
3_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.93851                            
4_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.90264                            
5_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.67482                            
ENmatResPreRec_FT_vsm_UMBAQE        6.0e-05                            
ENmatResPreRec_MD_vsm_UMBAQE        2.8e-06                            
                                    2_ENmatResPreRec_Hyb_vsm_UMBAQEtype
2_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
3_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.77976                            
4_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.76623                            
5_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.44392                            
ENmatResPreRec_FT_vsm_UMBAQE        2.2e-05                            
ENmatResPreRec_MD_vsm_UMBAQE        2.8e-06                            
                                    3_ENmatResPreRec_Hyb_vsm_UMBAQEtype
2_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
3_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
4_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.89411                            
5_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.63140                            
ENmatResPreRec_FT_vsm_UMBAQE        6.0e-05                            
ENmatResPreRec_MD_vsm_UMBAQE        2.8e-06                            
                                    4_ENmatResPreRec_Hyb_vsm_UMBAQEtype
2_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
3_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
4_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
5_ENmatResPreRec_Hyb_vsm_UMBAQEtype 0.77654                            
ENmatResPreRec_FT_vsm_UMBAQE        0.00014                            
ENmatResPreRec_MD_vsm_UMBAQE        4.2e-06                            
                                    5_ENmatResPreRec_Hyb_vsm_UMBAQEtype
2_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
3_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
4_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
5_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                                  
ENmatResPreRec_FT_vsm_UMBAQE        0.00041                            
ENmatResPreRec_MD_vsm_UMBAQE        2.9e-05                            
                                    ENmatResPreRec_FT_vsm_UMBAQE
2_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                           
3_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                           
4_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                           
5_ENmatResPreRec_Hyb_vsm_UMBAQEtype -                           
ENmatResPreRec_FT_vsm_UMBAQE        -                           
ENmatResPreRec_MD_vsm_UMBAQE        0.22244                     

P value adjustment method: BH