Campamentos 12 anos_2017

Paquetes

library("tidyverse")

Loading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
Conflicts with tidy packages ------------------------------------------------------------------------
filter(): dplyr, stats
lag():    dplyr, stats

abro mi df, denomino df12

df12 <- read.csv("campamentos 12 a<U+00F1>os.csv", header = TRUE, sep=",")
str(df12)

'data.frame':   21 obs. of  13 variables:
 $ n         : int  1 2 3 4 5 6 7 8 9 10 ...
 $ campamento: Factor w/ 5 levels "Futura Esperanza",..: 1 1 1 4 4 4 4 2 2 2 ...
 $ sexo      : Factor w/ 2 levels "F","M": 2 1 1 2 1 1 1 2 1 1 ...
 $ edad      : int  12 12 12 12 12 12 12 12 12 12 ...
 $ C         : int  1 4 2 0 0 1 0 0 0 0 ...
 $ P         : int  0 0 0 0 0 0 0 0 0 0 ...
 $ O         : int  0 0 0 0 0 0 2 2 2 0 ...
 $ COPD      : int  1 4 2 0 0 1 2 2 2 0 ...
 $ c         : int  NA NA NA NA NA 2 NA NA NA NA ...
 $ e         : int  NA NA NA NA NA 0 NA NA NA NA ...
 $ o         : int  NA NA NA NA NA 0 NA NA NA NA ...
 $ ceod      : int  NA NA NA NA NA 2 NA NA NA NA ...
 $ tto       : Factor w/ 3 levels "NO","SI","Si": 1 2 1 2 1 1 2 2 2 3 ...

summary(df12)

       n                 campamento sexo        edad          C                P    
 Min.   : 1   Futura Esperanza:3    F:11   Min.   :12   Min.   :0.0000   Min.   :0  
 1st Qu.: 6   Laderas         :4    M:10   1st Qu.:12   1st Qu.:0.0000   1st Qu.:0  
 Median :11   Mediaguas       :3           Median :12   Median :0.0000   Median :0  
 Mean   :11   Nuevo Amanecer  :4           Mean   :12   Mean   :0.8095   Mean   :0  
 3rd Qu.:16   Pelluhuin       :7           3rd Qu.:12   3rd Qu.:1.0000   3rd Qu.:0  
 Max.   :21                                Max.   :12   Max.   :4.0000   Max.   :0  
                                                                                    
       O               COPD             c             e            o            ceod    tto    
 Min.   :0.0000   Min.   :0.000   Min.   :0.0   Min.   :0    Min.   :0.0   Min.   :1    NO: 6  
 1st Qu.:0.0000   1st Qu.:0.000   1st Qu.:0.0   1st Qu.:0    1st Qu.:0.0   1st Qu.:2    SI:14  
 Median :0.0000   Median :2.000   Median :2.0   Median :0    Median :0.0   Median :2    Si: 1  
 Mean   :0.8095   Mean   :1.619   Mean   :1.4   Mean   :0    Mean   :0.6   Mean   :2           
 3rd Qu.:2.0000   3rd Qu.:2.000   3rd Qu.:2.0   3rd Qu.:0    3rd Qu.:1.0   3rd Qu.:2           
 Max.   :3.0000   Max.   :6.000   Max.   :3.0   Max.   :0    Max.   :2.0   Max.   :3           
                                  NA's   :16    NA's   :16   NA's   :16    NA's   :16          

Agrupo por campamento para nios de 12 aos y calculo media,de y mediana de COPD

agrupo por sexo en nios de 12 aos.

existe diferencia de ceod entre campamentos????

diferenciacampamentos

Call:
   aov(formula = df12$ceod ~ df12$campamento)

Terms:
                df12$campamento Residuals
Sum of Squares                0         2
Deg. of Freedom               1         3

Residual standard error: 0.8164966
Estimated effects may be unbalanced
16 observations deleted due to missingness

summary(diferenciacampamentos)

                Df Sum Sq Mean Sq F value Pr(>F)
df12$campamento  1      0  0.0000       0      1
Residuals        3      2  0.6667               
16 observations deleted due to missingness

lo mismo para COPD

diferenciacampamentos1 <- aov(df12$COPD~df12$campamento)
diferenciacampamentos1

summary(diferenciacampamentos1)

                Df Sum Sq Mean Sq F value Pr(>F)
df12$campamento  4   8.44   2.110   0.794  0.546
Residuals       16  42.51   2.657               

analizar entre tto por campamentos, existe diferencia ????

chisq.test(df12$tto,df12$campamento)

Chi-squared approximation may be incorrect

    Pearson's Chi-squared test

data:  df12$tto and df12$campamento
X-squared = 9.6488, df = 8, p-value = 0.2905

existe diferencia para el componente C del COPD entre campamentos????

diferenciacampamentosparacomp_c <- aov(df12$C~df12$campamento)
diferenciacampamentosparacomp_c 

summary(diferenciacampamentosparacomp_c)

                Df Sum Sq Mean Sq F value Pr(>F)
df12$campamento  4  8.976   2.244   1.613  0.219
Residuals       16 22.262   1.391               

Visualizo mis datos en grafico componente ceod segun sexo

Visualizo mis datos en grafico componente C del COPD segun sexo

grafico boxplot, para campamentos y COPD

grafico boxplot con ggplot2, para campamentos y componte c de ceod

Existe diferencia entre sexo para COPD

t.test(df12$COPD~df12$sexo)

    Welch Two Sample t-test

data:  df12$COPD by df12$sexo
t = -1.6346, df = 16.543, p-value = 0.121
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -2.5436554  0.3254736
sample estimates:
mean in group F mean in group M 
       1.090909        2.200000 

Existe diferencia entre sexo y componente c del COPD

t.test(df12$C~df12$sexo)

    Welch Two Sample t-test

data:  df12$C by df12$sexo
t = -0.6574, df = 18.909, p-value = 0.5188
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -1.5217600  0.7944873
sample estimates:
mean in group F mean in group M 
      0.6363636       1.0000000 

ahora hago analisis para COPD, existe diferencia en COPD por campamentos en nios de 12 aos?

diferenciacampamentoscopd <- aov(df12$COPD~df12$campamento)
diferenciacampamentoscopd

summary(diferenciacampamentoscopd)

                Df Sum Sq Mean Sq F value Pr(>F)
df12$campamento  4   8.44   2.110   0.794  0.546
Residuals       16  42.51   2.657               

diferencia para el componente C del COPD por campamento

diferenciacampamentosC<- aov(df12$C~df12$campamento)
diferenciacampamentosC

summary(diferenciacampamentosC)

                Df Sum Sq Mean Sq F value Pr(>F)
df12$campamento  4  8.976   2.244   1.613  0.219
Residuals       16 22.262   1.391