# P. aeruginosa <- read.csv ("P.aeruginosa_R.csv" , header = T, sep = ";" , dec = "." )str (P.aeruginosa)
'data.frame': 126 obs. of 3 variables:
$ Concentraciones: chr "C -" "C + " "1 mg/mL " "0.5 mg/mL " ...
$ Tiempo : int 0 0 0 0 0 0 0 0 0 0 ...
$ Absorbancia : num 0.082 0.068 0.1 0.09 0.108 0.091 0.082 0.077 0.067 0.096 ...
$ Tiempo= as.factor (P.aeruginosa$ Tiempo)library (FSA)Summarize (P.aeruginosa$ Absorbancia ~ P.aeruginosa$ Tiempo + P.aeruginosa$ Concentraciones)
P.aeruginosa$Tiempo P.aeruginosa$Concentraciones n mean sd min
1 0 0.05 mg/mL 3 0.0906667 0.0109697 0.082
2 24 0.05 mg/mL 3 0.7016667 0.0040415 0.697
3 48 0.05 mg/mL 3 0.9553333 0.0320832 0.922
4 72 0.05 mg/mL 3 1.1580000 0.0820731 1.078
5 96 0.05 mg/mL 3 1.0736667 0.2082218 0.836
6 120 0.05 mg/mL 3 1.1306667 0.3198395 0.762
7 0 0.1 mg/mL 3 0.0880000 0.0026458 0.086
8 24 0.1 mg/mL 3 0.7110000 0.0160000 0.695
9 48 0.1 mg/mL 3 0.8696667 0.0299388 0.849
10 72 0.1 mg/mL 3 1.0140000 0.1330451 0.914
11 96 0.1 mg/mL 3 1.0463333 0.2491312 0.802
12 120 0.1 mg/mL 3 1.1070000 0.2569883 0.838
13 0 0.25 mg/mL 3 0.0970000 0.0096437 0.090
14 24 0.25 mg/mL 3 0.7486667 0.0316280 0.723
15 48 0.25 mg/mL 3 0.8216667 0.0515978 0.772
16 72 0.25 mg/mL 3 0.8760000 0.0841249 0.784
17 96 0.25 mg/mL 3 0.9266667 0.1024809 0.817
18 120 0.25 mg/mL 3 0.9686667 0.1467526 0.841
19 0 0.5 mg/mL 3 0.0906667 0.0005774 0.090
20 24 0.5 mg/mL 3 0.7160000 0.0256320 0.692
21 48 0.5 mg/mL 3 0.8876667 0.0540031 0.855
22 72 0.5 mg/mL 3 0.9510000 0.0796994 0.903
23 96 0.5 mg/mL 3 1.0540000 0.1927096 0.833
24 120 0.5 mg/mL 3 1.1060000 0.2819858 0.782
25 0 1 mg/mL 3 0.0970000 0.0026458 0.095
26 24 1 mg/mL 3 0.7456667 0.0378594 0.719
27 48 1 mg/mL 3 1.0946667 0.0876375 1.010
28 72 1 mg/mL 3 1.1466667 0.0880473 1.045
29 96 1 mg/mL 3 0.7256667 0.0587310 0.685
30 120 1 mg/mL 3 0.6393333 0.0659116 0.567
31 0 C - 3 0.0800000 0.0026458 0.077
32 24 C - 3 0.8373333 0.0506392 0.794
33 48 C - 3 0.9083333 0.0614925 0.867
34 72 C - 3 0.9250000 0.0583866 0.885
35 96 C - 3 0.9253333 0.0632166 0.883
36 120 C - 3 1.0086667 0.1039920 0.911
37 0 C + 3 0.0680000 0.0010000 0.067
38 24 C + 3 0.0766667 0.0245425 0.062
39 48 C + 3 0.0756667 0.0236925 0.061
40 72 C + 3 0.0760000 0.0242693 0.061
41 96 C + 3 0.0806667 0.0265016 0.062
42 120 C + 3 0.0720000 0.0108167 0.063
Q1 median Q3 max
1 0.0845 0.087 0.0950 0.103
2 0.7005 0.704 0.7040 0.704
3 0.9400 0.958 0.9720 0.986
4 1.1160 1.154 1.1980 1.242
5 0.9985 1.161 1.1925 1.224
6 1.0290 1.296 1.3150 1.334
7 0.0865 0.087 0.0890 0.091
8 0.7030 0.711 0.7190 0.727
9 0.8525 0.856 0.8800 0.904
10 0.9385 0.963 1.0640 1.165
11 0.9195 1.037 1.1685 1.300
12 0.9855 1.133 1.2415 1.350
13 0.0915 0.093 0.1005 0.108
14 0.7310 0.739 0.7615 0.784
15 0.7950 0.818 0.8465 0.875
16 0.8395 0.895 0.9220 0.949
17 0.8800 0.943 0.9815 1.020
18 0.8885 0.936 1.0325 1.129
19 0.0905 0.091 0.0910 0.091
20 0.7025 0.713 0.7280 0.743
21 0.8565 0.858 0.9040 0.950
22 0.9050 0.907 0.9750 1.043
23 0.9875 1.142 1.1645 1.187
24 1.0110 1.240 1.2680 1.296
25 0.0955 0.096 0.0980 0.100
26 0.7240 0.729 0.7590 0.789
27 1.0495 1.089 1.1370 1.185
28 1.1210 1.197 1.1975 1.198
29 0.6920 0.699 0.7460 0.793
30 0.6110 0.655 0.6755 0.696
31 0.0790 0.081 0.0815 0.082
32 0.8095 0.825 0.8590 0.893
33 0.8730 0.879 0.9290 0.979
34 0.8915 0.898 0.9450 0.992
35 0.8890 0.895 0.9465 0.998
36 0.9540 0.997 1.0575 1.118
37 0.0675 0.068 0.0685 0.069
38 0.0625 0.063 0.0840 0.105
39 0.0620 0.063 0.0830 0.103
40 0.0620 0.063 0.0835 0.104
41 0.0655 0.069 0.0900 0.111
42 0.0660 0.069 0.0765 0.084
library (lattice)histogram (~ Absorbancia | Tiempo, data= P.aeruginosa,layout= c (1 ,3 )) histogram (~ Absorbancia | Concentraciones, data= P.aeruginosa,layout= c (1 ,3 )) ####### Tiempo 0 <- 0 <- subset (P.aeruginosa, P.aeruginosa$ Tiempo == tiempo_0)
Concentraciones Tiempo Absorbancia
1 C - 0 0.082
2 C + 0 0.068
3 1 mg/mL 0 0.100
4 0.5 mg/mL 0 0.090
5 0.25 mg/mL 0 0.108
6 0.1 mg/mL 0 0.091
7 0.05 mg/mL 0 0.082
8 C - 0 0.077
9 C + 0 0.067
10 1 mg/mL 0 0.096
11 0.5 mg/mL 0 0.091
12 0.25 mg/mL 0 0.090
13 0.1 mg/mL 0 0.087
14 0.05 mg/mL 0 0.087
15 C - 0 0.081
16 C + 0 0.069
17 1 mg/mL 0 0.095
18 0.5 mg/mL 0 0.091
19 0.25 mg/mL 0 0.093
20 0.1 mg/mL 0 0.086
21 0.05 mg/mL 0 0.103
# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_0$ Absorbancia ~ datos_0$ Concentraciones, data = datos_0)print (resultado_tiempo0)
Kruskal-Wallis rank sum test
data: datos_0$Absorbancia by datos_0$Concentraciones
Kruskal-Wallis chi-squared = 15.395, df = 6, p-value = 0.0174
# analisis post-hoc library (dunn.test)dunn.test (datos_0$ Absorbancia, datos_0$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 15.3947, df = 6, p-value = 0.02
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.296753
| 0.3833
|
0.25 mg/ | -0.824315 -1.121068
| 0.2049 0.1311
|
0.5 mg/m | -0.230808 -0.527561 0.593506
| 0.4087 0.2989 0.2764
|
1 mg/mL | -1.187013 -1.483767 -0.362698 -0.956205
| 0.1176 0.0689 0.3584 0.1695
|
C - | 1.351876 1.055123 2.176192 1.582685 2.538890
| 0.0882 0.1457 0.0148* 0.0567 0.0056*
|
C + | 1.978356 1.681603 2.802671 2.209164 3.165370 0.626479
| 0.0239* 0.0463 0.0025* 0.0136* 0.0008* 0.2655
alpha = 0.05
Reject Ho if p <= alpha/2
library (ggplot2)ggplot (datos_0, aes (x = datos_0$ Concentraciones, y = datos_0$ Absorbancia)) + geom_point () + labs (title = "Absorbancia vs Tiempo para diferentes Concentraciones" ,x = "Concentracion" ,y = "Absorbancia" ) + theme_minimal ()###### tiempo_24 <- 24 <- subset (P.aeruginosa, P.aeruginosa$ Tiempo == tiempo_24)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_24$ Absorbancia ~ datos_24$ Concentraciones, data = datos_24)print (resultado_tiempo24)
Kruskal-Wallis rank sum test
data: datos_24$Absorbancia by datos_24$Concentraciones
Kruskal-Wallis chi-squared = 16.184, df = 6, p-value = 0.0128
# analisis post-hoc dunn.test (datos_24$ Absorbancia, datos_24$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 16.1837, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -0.394899
| 0.3465
|
0.25 mg/ | -1.513780 -1.118881
| 0.0650 0.1316
|
0.5 mg/m | -0.592348 -0.197449 0.921431
| 0.2768 0.4217 0.1784
|
1 mg/mL | -1.447963 -1.053064 0.065816 -0.855615
| 0.0738 0.1462 0.4738 0.1961
|
C - | -2.566845 -2.171945 -1.053064 -1.974496 -1.118881
| 0.0051* 0.0149* 0.1462 0.0242* 0.1316
|
C + | 0.987248 1.382147 2.501028 1.579597 2.435212 3.554093
| 0.1618 0.0835 0.0062* 0.0571 0.0074* 0.0002*
alpha = 0.05
Reject Ho if p <= alpha/2
####### tiempo_48 <- 48 <- subset (P.aeruginosa, P.aeruginosa$ Tiempo == tiempo_48)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_48$ Absorbancia ~ datos_48$ Concentraciones, data = datos_48)print (resultado_tiempo48)
Kruskal-Wallis rank sum test
data: datos_48$Absorbancia by datos_48$Concentraciones
Kruskal-Wallis chi-squared = 16.693, df = 6, p-value = 0.01048
# analisis post-hoc dunn.test (datos_48$ Absorbancia, datos_48$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 16.6926, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 1.381698
| 0.0835
|
0.25 mg/ | 1.842264 0.460566
| 0.0327 0.3226
|
0.5 mg/m | 1.118517 -0.263180 -0.723746
| 0.1317 0.3962 0.2346
|
1 mg/mL | -0.789542 -2.171240 -2.631806 -1.908059
| 0.2149 0.0150* 0.0042* 0.0282
|
C - | 0.592156 -0.789542 -1.250108 -0.526361 1.381698
| 0.2769 0.2149 0.1056 0.2993 0.0835
|
C + | 2.763397 1.381698 0.921132 1.644879 3.552939 2.171240
| 0.0029* 0.0835 0.1785 0.0500 0.0002* 0.0150*
alpha = 0.05
Reject Ho if p <= alpha/2
###### tiempo_72 <- 72 <- subset (P.aeruginosa, P.aeruginosa$ Tiempo == tiempo_72)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_72$ Absorbancia ~ datos_72$ Concentraciones, data = datos_72)print (resultado_tiempo72)
Kruskal-Wallis rank sum test
data: datos_72$Absorbancia by datos_72$Concentraciones
Kruskal-Wallis chi-squared = 16.208, df = 6, p-value = 0.01268
# analisis post-hoc dunn.test (datos_72$ Absorbancia, datos_72$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 16.2078, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.921132
| 0.1785
|
0.25 mg/ | 2.171240 1.250108
| 0.0150* 0.1056
|
0.5 mg/m | 1.513288 0.592156 -0.657951
| 0.0651 0.2769 0.2553
|
1 mg/mL | 0.000000 -0.921132 -2.171240 -1.513288
| 0.5000 0.1785 0.0150* 0.0651
|
C - | 1.908059 0.986927 -0.263180 0.394771 1.908059
| 0.0282 0.1618 0.3962 0.3465 0.0282
|
C + | 3.158168 2.237035 0.986927 1.644879 3.158168 1.250108
| 0.0008* 0.0126* 0.1618 0.0500 0.0008* 0.1056
alpha = 0.05
Reject Ho if p <= alpha/2
####### tiempo_96 <- 96 <- subset (P.aeruginosa, P.aeruginosa$ Tiempo == tiempo_96)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_96$ Absorbancia ~ datos_96$ Concentraciones, data = datos_96)print (resultado_tiempo96)
Kruskal-Wallis rank sum test
data: datos_96$Absorbancia by datos_96$Concentraciones
Kruskal-Wallis chi-squared = 13.576, df = 6, p-value = 0.03475
# analisis post-hoc dunn.test (datos_96$ Absorbancia, datos_96$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 13.5758, df = 6, p-value = 0.03
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.263180
| 0.3962
|
0.25 mg/ | 0.789542 0.526361
| 0.2149 0.2993
|
0.5 mg/m | 0.197385 -0.065795 -0.592156
| 0.4218 0.4738 0.2769
|
1 mg/mL | 2.171240 1.908059 1.381698 1.973855
| 0.0150* 0.0282 0.0835 0.0242*
|
C - | 0.723746 0.460566 -0.065795 0.526361 -1.447493
| 0.2346 0.3226 0.4738 0.2993 0.0739
|
C + | 2.763397 2.500216 1.973855 2.566011 0.592156 2.039650
| 0.0029* 0.0062* 0.0242* 0.0051* 0.2769 0.0207*
alpha = 0.05
Reject Ho if p <= alpha/2
####### tiempo_120 <- 120 <- subset (P.aeruginosa, P.aeruginosa$ Tiempo == tiempo_120)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_120$ Absorbancia ~ datos_120$ Concentraciones, data = datos_120)print (resultado_tiempo120)
Kruskal-Wallis rank sum test
data: datos_120$Absorbancia by datos_120$Concentraciones
Kruskal-Wallis chi-squared = 13.251, df = 6, p-value = 0.03922
# analisis post-hoc dunn.test (datos_120$ Absorbancia, datos_120$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 13.251, df = 6, p-value = 0.04
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -0.032908
| 0.4869
|
0.25 mg/ | 0.559440 0.592348
| 0.2879 0.2768
|
0.5 mg/m | 0.131633 0.164541 -0.427807
| 0.4476 0.4347 0.3344
|
1 mg/mL | 2.007404 2.040312 1.447963 1.875771
| 0.0224* 0.0207* 0.0738 0.0303
|
C - | 0.493624 0.526532 -0.065816 0.361990 -1.513780
| 0.3108 0.2993 0.4738 0.3587 0.0650
|
C + | 2.599753 2.632661 2.040312 2.468120 0.592348 2.106129
| 0.0047* 0.0042* 0.0207* 0.0068* 0.2768 0.0176*
alpha = 0.05
Reject Ho if p <= alpha/2
# GRÁFICO ggplot (P.aeruginosa, aes (x = P.aeruginosa$ Tiempo, y = ifelse (P.aeruginosa$ Concentraciones == "C + " , NA , P.aeruginosa$ Absorbancia),color = factor (P.aeruginosa$ Concentraciones, levels = c ("C -" , "0.05 mg/mL" , "0.1 mg/mL" , "0.25 mg/mL" , "0.5 mg/mL " , "1 mg/mL " )), group = P.aeruginosa$ Concentraciones)) + stat_summary (fun = mean, geom = "line" , size = 0.5 , na.rm = TRUE ) + stat_summary (fun = mean, geom = "point" , size = 2 , na.rm = TRUE ) + stat_summary (fun.data = mean_sdl, fun.args = list (mult = 1 ), geom = "errorbar" , width = 0.1 ) + scale_y_continuous (name = "Absorbancia (modificada)" , limits = c (0 , 2 ), breaks = seq (0 , 2 , by = 0.5 )) + labs (y = "Absorbancia" , x = "Tiempo" , color = "Concentración" ) + theme_minimal ()
# S.aureus <- read.csv ("S.aureus_R.csv" , header = T, sep = ";" , dec = "." )str (S.aureus)
'data.frame': 126 obs. of 3 variables:
$ Concentraciones: chr "C -" "C + " "1 mg/mL " "0.5 mg/mL " ...
$ Tiempo : int 0 0 0 0 0 0 0 0 0 0 ...
$ Absorbancia : num 0.1 0.115 0.096 0.094 0.089 0.087 0.086 0.088 0.797 0.099 ...
$ Tiempo= as.factor (S.aureus$ Tiempo)library (FSA)Summarize (S.aureus$ Absorbancia ~ S.aureus$ Tiempo + S.aureus$ Concentraciones)
S.aureus$Tiempo S.aureus$Concentraciones n mean sd min Q1
1 0 0.05 mg/mL 3 0.0856667 0.0005774 0.085 0.0855
2 24 0.05 mg/mL 3 0.4336667 0.0102144 0.422 0.4300
3 48 0.05 mg/mL 3 0.5206667 0.0063509 0.517 0.5170
4 72 0.05 mg/mL 3 0.4556667 0.0257941 0.427 0.4450
5 96 0.05 mg/mL 3 0.4126667 0.0298385 0.393 0.3955
6 120 0.05 mg/mL 3 0.3743333 0.0656531 0.304 0.3445
7 0 0.1 mg/mL 3 0.0876667 0.0011547 0.087 0.0870
8 24 0.1 mg/mL 3 0.4276667 0.0277909 0.406 0.4120
9 48 0.1 mg/mL 3 0.5030000 0.0121244 0.492 0.4965
10 72 0.1 mg/mL 3 0.4393333 0.0433628 0.409 0.4145
11 96 0.1 mg/mL 3 0.4113333 0.0637207 0.356 0.3765
12 120 0.1 mg/mL 3 0.3636667 0.0909414 0.268 0.3210
13 0 0.25 mg/mL 3 0.0873333 0.0015275 0.086 0.0865
14 24 0.25 mg/mL 3 0.4526667 0.0075056 0.445 0.4490
15 48 0.25 mg/mL 3 0.4826667 0.0205994 0.461 0.4730
16 72 0.25 mg/mL 3 0.4270000 0.0095394 0.421 0.4215
17 96 0.25 mg/mL 3 0.3836667 0.0136137 0.373 0.3760
18 120 0.25 mg/mL 3 0.3200000 0.0137477 0.305 0.3140
19 0 0.5 mg/mL 3 0.0920000 0.0017321 0.091 0.0910
20 24 0.5 mg/mL 3 0.4813333 0.0213854 0.458 0.4720
21 48 0.5 mg/mL 3 0.5230000 0.0405093 0.483 0.5025
22 72 0.5 mg/mL 3 0.4850000 0.0589491 0.435 0.4525
23 96 0.5 mg/mL 3 0.4723333 0.0488092 0.427 0.4465
24 120 0.5 mg/mL 3 0.4196667 0.0290230 0.388 0.4070
25 0 1 mg/mL 3 0.0976667 0.0015275 0.096 0.0970
26 24 1 mg/mL 3 0.6930000 0.0406325 0.659 0.6705
27 48 1 mg/mL 3 0.7946667 0.0335609 0.767 0.7760
28 72 1 mg/mL 3 0.6613333 0.0361432 0.620 0.6485
29 96 1 mg/mL 3 0.6023333 0.0457967 0.551 0.5840
30 120 1 mg/mL 3 0.5516667 0.0642599 0.491 0.5180
31 0 C - 3 0.1060000 0.0216333 0.088 0.0940
32 24 C - 3 0.8286667 0.0950018 0.720 0.7950
33 48 C - 3 1.1766667 0.0744737 1.091 1.1520
34 72 C - 3 1.2356667 0.0563678 1.191 1.2040
35 96 C - 3 1.2726667 0.0220303 1.258 1.2600
36 120 C - 3 1.2963333 0.0040415 1.292 1.2945
37 0 C + 3 0.3423333 0.3937529 0.115 0.1150
38 24 C + 3 0.0763333 0.0159478 0.063 0.0675
39 48 C + 3 0.1860000 0.0217025 0.172 0.1735
40 72 C + 3 0.1986667 0.0203060 0.185 0.1870
41 96 C + 3 0.2190000 0.0204206 0.203 0.2075
42 120 C + 3 0.1996667 0.0176163 0.189 0.1895
median Q3 max
1 0.086 0.0860 0.086
2 0.438 0.4395 0.441
3 0.517 0.5225 0.528
4 0.463 0.4700 0.477
5 0.398 0.4225 0.447
6 0.385 0.4095 0.434
7 0.087 0.0880 0.089
8 0.418 0.4385 0.459
9 0.501 0.5085 0.516
10 0.420 0.4545 0.489
11 0.397 0.4390 0.481
12 0.374 0.4115 0.449
13 0.087 0.0880 0.089
14 0.453 0.4565 0.460
15 0.485 0.4935 0.502
16 0.422 0.4300 0.438
17 0.379 0.3890 0.399
18 0.323 0.3275 0.332
19 0.091 0.0925 0.094
20 0.486 0.4930 0.500
21 0.522 0.5430 0.564
22 0.470 0.5100 0.550
23 0.466 0.4950 0.524
24 0.426 0.4355 0.445
25 0.098 0.0985 0.099
26 0.682 0.7100 0.738
27 0.785 0.8085 0.832
28 0.677 0.6820 0.687
29 0.617 0.6280 0.639
30 0.545 0.5820 0.619
31 0.100 0.1150 0.130
32 0.870 0.8830 0.896
33 1.213 1.2195 1.226
34 1.217 1.2580 1.299
35 1.262 1.2800 1.298
36 1.297 1.2985 1.300
37 0.115 0.4560 0.797
38 0.072 0.0830 0.094
39 0.175 0.1930 0.211
40 0.189 0.2055 0.222
41 0.212 0.2270 0.242
42 0.190 0.2050 0.220
######## Tiempo 0 # Cambia esto al tiempo que desees analizar <- 0 <- subset (S.aureus, S.aureus$ Tiempo == tiempo_0)
Concentraciones Tiempo Absorbancia
1 C - 0 0.100
2 C + 0 0.115
3 1 mg/mL 0 0.096
4 0.5 mg/mL 0 0.094
5 0.25 mg/mL 0 0.089
6 0.1 mg/mL 0 0.087
7 0.05 mg/mL 0 0.086
8 C - 0 0.088
9 C + 0 0.797
10 1 mg/mL 0 0.099
11 0.5 mg/mL 0 0.091
12 0.25 mg/mL 0 0.087
13 0.1 mg/mL 0 0.087
14 0.05 mg/mL 0 0.085
15 C - 0 0.130
16 C + 0 0.115
17 1 mg/mL 0 0.098
18 0.5 mg/mL 0 0.091
19 0.25 mg/mL 0 0.086
20 0.1 mg/mL 0 0.089
21 0.05 mg/mL 0 0.086
# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_0$ Absorbancia ~ datos_0$ Concentraciones, data = datos_0)print (resultado_tiempo0)
Kruskal-Wallis rank sum test
data: datos_0$Absorbancia by datos_0$Concentraciones
Kruskal-Wallis chi-squared = 16.922, df = 6, p-value = 0.009575
# analisis post-hoc library (dunn.test)dunn.test (datos_0$ Absorbancia, datos_0$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 16.9217, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -0.957455
| 0.1692
|
0.25 mg/ | -0.759361 0.198094
| 0.2238 0.4215
|
0.5 mg/m | -1.914911 -0.957455 -1.155549
| 0.0278 0.1692 0.1239
|
1 mg/mL | -2.509193 -1.551738 -1.749832 -0.594282
| 0.0061* 0.0604 0.0401 0.2762
|
C - | -2.509193 -1.551738 -1.749832 -0.594282 0.000000
| 0.0061* 0.0604 0.0401 0.2762 0.5000
|
C + | -3.367602 -2.410146 -2.608241 -1.452691 -0.858408 -0.858408
| 0.0004* 0.0080* 0.0046* 0.0732 0.1953 0.1953
alpha = 0.05
Reject Ho if p <= alpha/2
######## tiempo_24 <- 24 <- subset (S.aureus, S.aureus$ Tiempo == tiempo_24)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_24$ Absorbancia ~ datos_24$ Concentraciones, data = datos_24)print (resultado_tiempo24)
Kruskal-Wallis rank sum test
data: datos_24$Absorbancia by datos_24$Concentraciones
Kruskal-Wallis chi-squared = 18.216, df = 6, p-value = 0.005713
# analisis post-hoc dunn.test (datos_24$ Absorbancia, datos_24$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 18.2165, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.000000
| 0.5000
|
0.25 mg/ | -0.723746 -0.723746
| 0.2346 0.2346
|
0.5 mg/m | -1.250108 -1.250108 -0.526361
| 0.1056 0.1056 0.2993
|
1 mg/mL | -2.039650 -2.039650 -1.315903 -0.789542
| 0.0207* 0.0207* 0.0941 0.2149
|
C - | -2.500216 -2.500216 -1.776469 -1.250108 -0.460566
| 0.0062* 0.0062* 0.0378 0.1056 0.3226
|
C + | 0.986927 0.986927 1.710674 2.237035 3.026577 3.487143
| 0.1618 0.1618 0.0436 0.0126* 0.0012* 0.0002*
alpha = 0.05
Reject Ho if p <= alpha/2
######## tiempo_48 <- 48 <- subset (S.aureus, S.aureus$ Tiempo == tiempo_48)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_48$ Absorbancia ~ datos_48$ Concentraciones, data = datos_48)print (resultado_tiempo48)
Kruskal-Wallis rank sum test
data: datos_48$Absorbancia by datos_48$Concentraciones
Kruskal-Wallis chi-squared = 17.83, df = 6, p-value = 0.006672
# analisis post-hoc dunn.test (datos_48$ Absorbancia, datos_48$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 17.8298, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.789798
| 0.2148
|
0.25 mg/ | 1.184697 0.394899
| 0.1181 0.3465
|
0.5 mg/m | 0.263266 -0.526532 -0.921431
| 0.3962 0.2993 0.1784
|
1 mg/mL | -0.921431 -1.711230 -2.106129 -1.184697
| 0.1784 0.0435 0.0176* 0.1181
|
C - | -1.513780 -2.303578 -2.698478 -1.777046 -0.592348
| 0.0650 0.0106* 0.0035* 0.0378 0.2768
|
C + | 2.040312 1.250514 0.855615 1.777046 2.961744 3.554093
| 0.0207* 0.1056 0.1961 0.0378 0.0015* 0.0002*
alpha = 0.05
Reject Ho if p <= alpha/2
######## tiempo_72 <- 72 <- subset (S.aureus, S.aureus$ Tiempo == tiempo_72)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_72$ Absorbancia ~ datos_72$ Concentraciones, data = datos_72)print (resultado_tiempo72)
Kruskal-Wallis rank sum test
data: datos_72$Absorbancia by datos_72$Concentraciones
Kruskal-Wallis chi-squared = 17.247, df = 6, p-value = 0.008418
# analisis post-hoc dunn.test (datos_72$ Absorbancia, datos_72$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 17.2468, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.592156
| 0.2769
|
0.25 mg/ | 0.592156 0.000000
| 0.2769 0.5000
|
0.5 mg/m | -0.263180 -0.855337 -0.855337
| 0.3962 0.1962 0.1962
|
1 mg/mL | -1.250108 -1.842264 -1.842264 -0.986927
| 0.1056 0.0327 0.0327 0.1618
|
C - | -1.842264 -2.434421 -2.434421 -1.579084 -0.592156
| 0.0327 0.0075* 0.0075* 0.0572 0.2769
|
C + | 1.710674 1.118517 1.118517 1.973855 2.960782 3.552939
| 0.0436 0.1317 0.1317 0.0242* 0.0015* 0.0002*
alpha = 0.05
Reject Ho if p <= alpha/2
######## tiempo_96 <- 96 <- subset (S.aureus, S.aureus$ Tiempo == tiempo_96)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_96$ Absorbancia ~ datos_96$ Concentraciones, data = datos_96)print (resultado_tiempo96)
Kruskal-Wallis rank sum test
data: datos_96$Absorbancia by datos_96$Concentraciones
Kruskal-Wallis chi-squared = 17.628, df = 6, p-value = 0.007233
# analisis post-hoc dunn.test (datos_96$ Absorbancia, datos_96$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 17.6277, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.131590
| 0.4477
|
0.25 mg/ | 0.460566 0.328975
| 0.3226 0.3711
|
0.5 mg/m | -0.723746 -0.855337 -1.184313
| 0.2346 0.1962 0.1181
|
1 mg/mL | -1.513288 -1.644879 -1.973855 -0.789542
| 0.0651 0.0500 0.0242* 0.2149
|
C - | -2.105445 -2.237035 -2.566011 -1.381698 -0.592156
| 0.0176* 0.0126* 0.0051* 0.0835 0.2769
|
C + | 1.447493 1.315903 0.986927 2.171240 2.960782 3.552939
| 0.0739 0.0941 0.1618 0.0150* 0.0015* 0.0002*
alpha = 0.05
Reject Ho if p <= alpha/2
####### tiempo_120 <- 120 <- subset (S.aureus, S.aureus$ Tiempo == tiempo_120)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_120$ Absorbancia ~ datos_120$ Concentraciones, data = datos_120)print (resultado_tiempo120)
Kruskal-Wallis rank sum test
data: datos_120$Absorbancia by datos_120$Concentraciones
Kruskal-Wallis chi-squared = 17.247, df = 6, p-value = 0.008418
# analisis post-hoc dunn.test (datos_120$ Absorbancia, datos_120$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 17.2468, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.000000
| 0.5000
|
0.25 mg/ | 0.460566 0.460566
| 0.3226 0.3226
|
0.5 mg/m | -0.592156 -0.592156 -1.052722
| 0.2769 0.2769 0.1462
|
1 mg/mL | -1.513288 -1.513288 -1.973855 -0.921132
| 0.0651 0.0651 0.0242* 0.1785
|
C - | -2.105445 -2.105445 -2.566011 -1.513288 -0.592156
| 0.0176* 0.0176* 0.0051* 0.0651 0.2769
|
C + | 1.447493 1.447493 0.986927 2.039650 2.960782 3.552939
| 0.0739 0.0739 0.1618 0.0207* 0.0015* 0.0002*
alpha = 0.05
Reject Ho if p <= alpha/2
# GRÁFICO ggplot (S.aureus, aes (x = S.aureus$ Tiempo, y = ifelse (S.aureus$ Concentraciones == "C + " , NA , S.aureus$ Absorbancia),color = factor (S.aureus$ Concentraciones, levels = c ("C -" , "0.05 mg/mL" , "0.1 mg/mL" , "0.25 mg/mL" , "0.5 mg/mL " , "1 mg/mL " )), group = S.aureus$ Concentraciones)) + stat_summary (fun = mean, geom = "line" , size = 0.5 , na.rm = TRUE ) + stat_summary (fun = mean, geom = "point" , size = 2 , na.rm = TRUE ) + stat_summary (fun.data = mean_sdl, fun.args = list (mult = 1 ), geom = "errorbar" , width = 0.1 ) + labs (y = "Absorbancia" , x = "Tiempo" , color = "Concentración" ) + theme_minimal ()
# C.albicans <- read.csv ("C.albicans_R.csv" , header = T, sep = ";" , dec = "." )str (C.albicans)
'data.frame': 126 obs. of 3 variables:
$ Concentraciones: chr "C -" "C + " "1 mg/mL " "0.5 mg/mL " ...
$ Tiempo : int 0 0 0 0 0 0 0 0 0 0 ...
$ Absorbancia : num 0.076 0.102 0.096 0.089 0.088 0.092 0.09 0.087 0.104 0.098 ...
$ Tiempo= as.factor (C.albicans$ Tiempo)library (FSA)Summarize (C.albicans$ Absorbancia ~ C.albicans$ Tiempo + C.albicans$ Concentraciones)
C.albicans$Tiempo C.albicans$Concentraciones n mean sd min
1 0 0.05 mg/mL 3 0.0886667 0.0023094 0.086
2 24 0.05 mg/mL 3 0.2693333 0.0249065 0.253
3 48 0.05 mg/mL 3 0.4463333 0.0690821 0.403
4 72 0.05 mg/mL 3 0.6000000 0.0475710 0.554
5 96 0.05 mg/mL 3 0.6340000 0.1003544 0.559
6 120 0.05 mg/mL 3 0.6466667 0.0996059 0.566
7 0 0.1 mg/mL 3 0.0916667 0.0035119 0.088
8 24 0.1 mg/mL 3 0.3433333 0.0780150 0.291
9 48 0.1 mg/mL 3 0.5076667 0.0346747 0.469
10 72 0.1 mg/mL 3 0.5836667 0.0192180 0.563
11 96 0.1 mg/mL 3 0.6350000 0.0452990 0.587
12 120 0.1 mg/mL 3 0.6733333 0.0771514 0.605
13 0 0.25 mg/mL 3 0.0883333 0.0005774 0.088
14 24 0.25 mg/mL 3 0.3246667 0.0085049 0.316
15 48 0.25 mg/mL 3 0.4556667 0.0025166 0.453
16 72 0.25 mg/mL 3 0.5126667 0.0607810 0.446
17 96 0.25 mg/mL 3 0.5500000 0.0721942 0.468
18 120 0.25 mg/mL 3 0.5720000 0.0752861 0.486
19 0 0.5 mg/mL 3 0.0900000 0.0045826 0.086
20 24 0.5 mg/mL 3 0.3103333 0.0127017 0.303
21 48 0.5 mg/mL 3 0.4753333 0.0427122 0.427
22 72 0.5 mg/mL 3 0.5256667 0.0435928 0.500
23 96 0.5 mg/mL 3 0.6203333 0.0665307 0.571
24 120 0.5 mg/mL 3 0.6486667 0.0446356 0.609
25 0 1 mg/mL 3 0.0966667 0.0011547 0.096
26 24 1 mg/mL 3 0.3070000 0.0419404 0.269
27 48 1 mg/mL 3 0.4996667 0.0353883 0.460
28 72 1 mg/mL 3 0.6926667 0.1220833 0.552
29 96 1 mg/mL 3 0.8306667 0.1021094 0.713
30 120 1 mg/mL 3 0.8720000 0.0780833 0.784
31 0 C - 3 0.0816667 0.0055076 0.076
32 24 C - 3 0.6386667 0.0472582 0.602
33 48 C - 3 0.8250000 0.0619919 0.756
34 72 C - 3 0.9916667 0.0525959 0.934
35 96 C - 3 1.0300000 0.0888313 0.935
36 120 C - 3 1.0940000 0.0459021 1.045
37 0 C + 3 0.1086667 0.0098658 0.102
38 24 C + 3 0.2606667 0.0150111 0.252
39 48 C + 3 0.4000000 0.0915369 0.307
40 72 C + 3 0.4623333 0.0822091 0.369
41 96 C + 3 0.5616667 0.0875233 0.462
42 120 C + 3 0.6206667 0.1240739 0.479
Q1 median Q3 max
1 0.0880 0.090 0.0900 0.090
2 0.2550 0.257 0.2775 0.298
3 0.4065 0.410 0.4680 0.526
4 0.5755 0.597 0.6230 0.649
5 0.5770 0.595 0.6715 0.748
6 0.5910 0.616 0.6870 0.758
7 0.0900 0.092 0.0935 0.095
8 0.2985 0.306 0.3695 0.433
9 0.4935 0.518 0.5270 0.536
10 0.5750 0.587 0.5940 0.601
11 0.6140 0.641 0.6590 0.677
12 0.6315 0.658 0.7075 0.757
13 0.0880 0.088 0.0885 0.089
14 0.3205 0.325 0.3290 0.333
15 0.4545 0.456 0.4570 0.458
16 0.4865 0.527 0.5460 0.565
17 0.5230 0.578 0.5910 0.604
18 0.5450 0.604 0.6150 0.626
19 0.0875 0.089 0.0920 0.095
20 0.3030 0.303 0.3140 0.325
21 0.4590 0.491 0.4995 0.508
22 0.5005 0.501 0.5385 0.576
23 0.5825 0.594 0.6450 0.696
24 0.6245 0.640 0.6685 0.697
25 0.0960 0.096 0.0970 0.098
26 0.2845 0.300 0.3260 0.352
27 0.4855 0.511 0.5195 0.528
28 0.6535 0.755 0.7630 0.771
29 0.7980 0.883 0.8895 0.896
30 0.8415 0.899 0.9160 0.933
31 0.0790 0.082 0.0845 0.087
32 0.6120 0.622 0.6570 0.692
33 0.7995 0.843 0.8595 0.876
34 0.9690 1.004 1.0205 1.037
35 0.9895 1.044 1.0775 1.111
36 1.0730 1.101 1.1185 1.136
37 0.1030 0.104 0.1120 0.120
38 0.2520 0.252 0.2650 0.278
39 0.3550 0.403 0.4465 0.490
40 0.4315 0.494 0.5090 0.524
41 0.5295 0.597 0.6115 0.626
42 0.5760 0.673 0.6915 0.710
# Tiempo 0 # Cambia esto al tiempo que desees analizar <- 0 <- subset (C.albicans, C.albicans$ Tiempo == tiempo_0)
Concentraciones Tiempo Absorbancia
1 C - 0 0.076
2 C + 0 0.102
3 1 mg/mL 0 0.096
4 0.5 mg/mL 0 0.089
5 0.25 mg/mL 0 0.088
6 0.1 mg/mL 0 0.092
7 0.05 mg/mL 0 0.090
8 C - 0 0.087
9 C + 0 0.104
10 1 mg/mL 0 0.098
11 0.5 mg/mL 0 0.086
12 0.25 mg/mL 0 0.088
13 0.1 mg/mL 0 0.088
14 0.05 mg/mL 0 0.090
15 C - 0 0.082
16 C + 0 0.120
17 1 mg/mL 0 0.096
18 0.5 mg/mL 0 0.095
19 0.25 mg/mL 0 0.089
20 0.1 mg/mL 0 0.095
21 0.05 mg/mL 0 0.086
# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_0$ Absorbancia ~ datos_0$ Concentraciones, data = datos_0)print (resultado_tiempo0)
Kruskal-Wallis rank sum test
data: datos_0$Absorbancia by datos_0$Concentraciones
Kruskal-Wallis chi-squared = 16.051, df = 6, p-value = 0.01349
# analisis post-hoc library (dunn.test)dunn.test (datos_0$ Absorbancia, datos_0$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 16.0505, df = 6, p-value = 0.01
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -0.527906
| 0.2988
|
0.25 mg/ | 0.197964 0.725871
| 0.4215 0.2340
|
0.5 mg/m | -0.065988 0.461917 -0.263953
| 0.4737 0.3221 0.3959
|
1 mg/mL | -1.616712 -1.088806 -1.814677 -1.550724
| 0.0530 0.1381 0.0348 0.0605
|
C - | 1.220783 1.748689 1.022818 1.286771 2.837495
| 0.1111 0.0402 0.1532 0.0991 0.0023*
|
C + | -2.210607 -1.682701 -2.408572 -2.144618 -0.593894 -3.431390
| 0.0135* 0.0462 0.0080* 0.0160* 0.2763 0.0003*
alpha = 0.05
Reject Ho if p <= alpha/2
######## tiempo_24 <- 24 <- subset (C.albicans, C.albicans$ Tiempo == tiempo_24)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_24$ Absorbancia ~ datos_24$ Concentraciones, data = datos_24)print (resultado_tiempo24)
Kruskal-Wallis rank sum test
data: datos_24$Absorbancia by datos_24$Concentraciones
Kruskal-Wallis chi-squared = 15.316, df = 6, p-value = 0.01794
# analisis post-hoc dunn.test (datos_24$ Absorbancia, datos_24$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 15.3155, df = 6, p-value = 0.02
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -1.448905
| 0.0737
|
0.25 mg/ | -1.876991 -0.428085
| 0.0303 0.3343
|
0.5 mg/m | -1.350116 0.098789 0.526874
| 0.0885 0.4607 0.2991
|
1 mg/mL | -1.053749 0.395156 0.823241 0.296367
| 0.1460 0.3464 0.2052 0.3835
|
C - | -2.963670 -1.514765 -1.086679 -1.613554 -1.909921
| 0.0015* 0.0649 0.1386 0.0533 0.0281
|
C + | 0.395156 1.844061 2.272147 1.745272 1.448905 3.358826
| 0.3464 0.0326 0.0115* 0.0405 0.0737 0.0004*
alpha = 0.05
Reject Ho if p <= alpha/2
####### tiempo_48 <- 48 <- subset (C.albicans, C.albicans$ Tiempo == tiempo_48)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_48$ Absorbancia ~ datos_48$ Concentraciones, data = datos_48)print (resultado_tiempo48)
Kruskal-Wallis rank sum test
data: datos_48$Absorbancia by datos_48$Concentraciones
Kruskal-Wallis chi-squared = 12.853, df = 6, p-value = 0.04544
# analisis post-hoc dunn.test (datos_48$ Absorbancia, datos_48$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 12.8525, df = 6, p-value = 0.05
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -1.349239
| 0.0886
|
0.25 mg/ | 0.098724 1.447963
| 0.4607 0.0738
|
0.5 mg/m | -0.493624 0.855615 -0.592348
| 0.3108 0.1961 0.2768
|
1 mg/mL | -1.151789 0.197449 -1.250514 -0.658165
| 0.1247 0.4217 0.1056 0.2552
|
C - | -2.468120 -1.118881 -2.566845 -1.974496 -1.316330
| 0.0068* 0.1316 0.0051* 0.0242* 0.0940
|
C + | 0.526532 1.875771 0.427807 1.020156 1.678321 2.994652
| 0.2993 0.0303 0.3344 0.1538 0.0466 0.0014*
alpha = 0.05
Reject Ho if p <= alpha/2
######### tiempo_72 <- 72 <- subset (C.albicans, C.albicans$ Tiempo == tiempo_72)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_72$ Absorbancia ~ datos_72$ Concentraciones, data = datos_72)print (resultado_tiempo72)
Kruskal-Wallis rank sum test
data: datos_72$Absorbancia by datos_72$Concentraciones
Kruskal-Wallis chi-squared = 14.996, df = 6, p-value = 0.02029
# analisis post-hoc dunn.test (datos_72$ Absorbancia, datos_72$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 14.9957, df = 6, p-value = 0.02
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | 0.065795
| 0.4738
|
0.25 mg/ | 1.250108 1.184313
| 0.1056 0.1181
|
0.5 mg/m | 1.184313 1.118517 -0.065795
| 0.1181 0.1317 0.4738
|
1 mg/mL | -0.263180 -0.328975 -1.513288 -1.447493
| 0.3962 0.3711 0.0651 0.0739
|
C - | -1.381698 -1.447493 -2.631806 -2.566011 -1.118517
| 0.0835 0.0739 0.0042* 0.0051* 0.1317
|
C + | 1.908059 1.842264 0.657951 0.723746 2.171240 3.289758
| 0.0282 0.0327 0.2553 0.2346 0.0150* 0.0005*
alpha = 0.05
Reject Ho if p <= alpha/2
###### tiempo_96 <- 96 <- subset (C.albicans, C.albicans$ Tiempo == tiempo_96)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_96$ Absorbancia ~ datos_96$ Concentraciones, data = datos_96)print (resultado_tiempo96)
Kruskal-Wallis rank sum test
data: datos_96$Absorbancia by datos_96$Concentraciones
Kruskal-Wallis chi-squared = 13.177, df = 6, p-value = 0.0403
# analisis post-hoc dunn.test (datos_96$ Absorbancia, datos_96$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 13.1775, df = 6, p-value = 0.04
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -0.263180
| 0.3962
|
0.25 mg/ | 0.657951 0.921132
| 0.2553 0.1785
|
0.5 mg/m | 0.131590 0.394771 -0.526361
| 0.4477 0.3465 0.2993
|
1 mg/mL | -1.513288 -1.250108 -2.171240 -1.644879
| 0.0651 0.1056 0.0150* 0.0500
|
C - | -2.171240 -1.908059 -2.829192 -2.302830 -0.657951
| 0.0150* 0.0282 0.0023* 0.0106* 0.2553
|
C + | 0.394771 0.657951 -0.263180 0.263180 1.908059 2.566011
| 0.3465 0.2553 0.3962 0.3962 0.0282 0.0051*
alpha = 0.05
Reject Ho if p <= alpha/2
###### tiempo_120 <- 120 <- subset (C.albicans, C.albicans$ Tiempo == tiempo_120)# Realizar el análisis de Kruskal-Wallis <- kruskal.test (datos_120$ Absorbancia ~ datos_120$ Concentraciones, data = datos_120)print (resultado_tiempo120)
Kruskal-Wallis rank sum test
data: datos_120$Absorbancia by datos_120$Concentraciones
Kruskal-Wallis chi-squared = 13.801, df = 6, p-value = 0.03194
# analisis post-hoc dunn.test (datos_120$ Absorbancia, datos_120$ Concentraciones)
Kruskal-Wallis rank sum test
data: x and group
Kruskal-Wallis chi-squared = 13.8009, df = 6, p-value = 0.03
Comparison of x by group
(No adjustment)
Col Mean-|
Row Mean | 0.05 mg/ 0.1 mg/m 0.25 mg/ 0.5 mg/m 1 mg/mL C -
---------+------------------------------------------------------------------
0.1 mg/m | -0.263180
| 0.3962
|
0.25 mg/ | 0.723746 0.986927
| 0.2346 0.1618
|
0.5 mg/m | -0.131590 0.131590 -0.855337
| 0.4477 0.4477 0.1962
|
1 mg/mL | -1.710674 -1.447493 -2.434421 -1.579084
| 0.0436 0.0739 0.0075* 0.0572
|
C - | -2.302830 -2.039650 -3.026577 -2.171240 -0.592156
| 0.0106* 0.0207* 0.0012* 0.0150* 0.2769
|
C + | 0.000000 0.263180 -0.723746 0.131590 1.710674 2.302830
| 0.5000 0.3962 0.2346 0.4477 0.0436 0.0106*
alpha = 0.05
Reject Ho if p <= alpha/2
#### Gráfico ggplot (C.albicans, aes (x = C.albicans$ Tiempo, y = ifelse (C.albicans$ Concentraciones == "C + " , NA , C.albicans$ Absorbancia),color = factor (C.albicans$ Concentraciones, levels = c ("C -" , "0.05 mg/mL" , "0.1 mg/mL" , "0.25 mg/mL" , "0.5 mg/mL " , "1 mg/mL " )), group = C.albicans$ Concentraciones)) + stat_summary (fun = mean, geom = "line" , size = 0.5 , na.rm = TRUE ) + stat_summary (fun = mean, geom = "point" , size = 2 , na.rm = TRUE ) + stat_summary (fun.data = mean_sdl, fun.args = list (mult = 1 ), geom = "errorbar" , width = 0.1 ) + labs (y = "Absorbancia (nm)" , x = "Tiempo (Horas)" , color = "Concentración" ) + theme_minimal ()
Hallando el Concentración minima inhibitoria para los datos de S.aureus y para C. albicans en el tiempo de 24 horas
# S.aureus <- subset (datos_24, datos_24$ Concentraciones %in% c ("0.05 mg/mL" , "0.1 mg/mL" , "0.25 mg/mL" , "0.5 mg/mL " , "1 mg/mL " ))library (dplyr)
Adjuntando el paquete: 'dplyr'
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
# concentracion minima inhibitoria S.aureus <- Cons.S.aureus %>% filter (Cons.S.aureus$ Absorbancia <= 0.1 ) %>% summarise (CMI = min (Cons.S.aureus$ Concentraciones))print (cmi)# se guarda como Cons.S.aureus1 para poder hacer la gráfica # GRÁFICA # se cragan los datos <- read.csv ("Cons.S.aureus1.csv" , header = T, sep = ";" , dec = "." )str (Cons.S.aureus1)
'data.frame': 15 obs. of 3 variables:
$ Concentraciones: num 1 0.5 0.25 0.1 0.05 1 0.5 0.25 0.1 0.05 ...
$ Tiempo : int 24 24 24 24 24 24 24 24 24 24 ...
$ Absorbancia : num 0.789 0.692 0.723 0.727 0.704 0.729 0.743 0.784 0.711 0.704 ...
<- Cons.S.aureus1 %>% group_by (Concentraciones) %>% summarise (media_absorbancia = mean (Absorbancia),desviacion_absorbancia = sd (Absorbancia)# Grafico de los datos ggplot (resumen, aes (x = Concentraciones, y = media_absorbancia)) + geom_point (size = 2 ) + geom_errorbar (aes (ymin = media_absorbancia - desviacion_absorbancia, ymax = media_absorbancia + desviacion_absorbancia), width = 0.02 ) + scale_y_continuous (name = "Absorbancia (modificada)" , limits = c (0.6 , 1 ), breaks = seq (0.6 , 1 , by = 0.1 )) + labs (x = "Concentración (mg/L)" , y = "Absorbancia" , title = "Curva de Inhibición del Crecimiento Bacteriano" ) + theme_minimal ()
