Probabilidade e Estatística - Engenharia 2º ano - AEDB

Resultado da avaliação de Probabilidade e Estatística - Engenharia 2A e 2B - AEDB

4º Bimestre - 2017

---

rm(list=ls(all=TRUE))
library(readxl)
notas <- read_excel("notas.xlsx")
#notas$notas <-notas$notas/10

Tabulação das Notas por Turma

library(psych)
table(notas)

     turma
notas ENG_2A ENG_2B
  0        2      4
  2        0      1
  2.5      0      2
  3        4      3
  3.3      1      0
  3.5      0      2
  3.8      1      0
  4        3      9
  4.5      7      7
  5        4      1
  5.4      1      0
  5.5      9      4
  5.7      1      0
  6        4      5
  6.1      1      0
  6.3      3      0
  6.5      1      2
  6.7      1      0
  6.8      1      0
  7        4      7
  7.3      3      0
  7.5      2      1
  8        7      2
  8.3      1      0
  8.5      3      1
  8.8      1      0
  9        2      1
  9.5      2      1
  10       2      5

library("graphics")
### Mosaic plot of observed values
mosaicplot(table(notas),  las=2, col="steelblue",
           main = "Tabulação das notas")

Sumário - Turmas 2A e 2B

describeBy(notas$notas, notas$turma)

 Descriptive statistics by group 
group: ENG_2A
   vars  n mean   sd median trimmed  mad min max range  skew kurtosis   se
X1    1 71 6.09 2.08      6    6.17 2.22   0  10    10 -0.45     0.36 0.25
---------------------------------------------------------------------------------- 
group: ENG_2B
   vars  n mean   sd median trimmed  mad min max range  skew kurtosis   se
X1    1 58 5.34 2.58   5.25    5.38 2.59   0  10    10 -0.03    -0.35 0.34

Sumário - Todos os alunos

psych::describe(notas$notas)

   vars   n mean   sd median trimmed  mad min max range  skew kurtosis   se
X1    1 129 5.76 2.34    5.5    5.81 2.22   0  10    10 -0.29    -0.01 0.21

library(ggplot2)
a <- ggplot(notas, aes(x = notas))
#histogram Eng
# Position adjustment: "identity" (overlaid)
#a + geom_histogram(breaks=seq(0,10,1),aes(color = turma), fill = "white", alpha = 0.4,position="identity", closed #= c("left"))+
#  scale_x_continuous(limits = c(0,10), breaks=seq(0,10,1))+
#  theme_minimal()+
#  xlab("Notas")+
#  ylab("Frequência")+
#  ggtitle("Histograma por turmas (Eng 2A e 2B)")
  
#histogram Eng
plot <- ggplot(data=notas, aes(x=notas)) + geom_histogram(breaks=seq(0,10,1),fill="royalblue", colour="black", alpha=.4, closed = c("left"))
plot <- plot + xlab("Notas")+
  ylab("Frequência")+
  ggtitle("Histograma das turmas Eng 2A e 2B")+
  theme(plot.title=element_text(size=rel(1), lineheight=.9,face="bold.italic", colour="black"))+
  theme(axis.title=element_text(size=12, lineheight=.9, face="bold", colour="black"))+
  stat_bin(bins=10, binwidth = 1,breaks=seq(0,10,1), geom="text", aes(label=..count..), vjust=-1, closed = c("left"))+ scale_x_continuous(limits = c(0,10), breaks=seq(0,10,1))+
  scale_y_continuous(expand = c(0,0),limits = c(0,max(ggplot_build(plot)$data[[1]]$count)*1.1),  breaks=seq(0,max(ggplot_build(plot)$data[[1]]$count)*1.1,10)) 
plot

a + geom_dotplot(aes(fill = turma),binpositions = "all")+
  theme_minimal()

# Box plot with mean points
e <- ggplot(notas, aes(x = turma, y = notas))
e + geom_boxplot(aes(color = turma,fill = turma)) +
stat_summary(fun.y = mean, geom = "point",
shape = 18, size = 4, color = "blue")+
  scale_color_brewer(palette="Dark2")+
  theme_minimal()

# Change point colors by dose (groups)
e + geom_jitter(aes(color = turma), position = position_jitter(0.3)) +
theme_minimal()

library(ggpubr)  #http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/
ggdensity(notas, x = "notas",
   add = "mean", rug = TRUE,
   color = "turma", fill = "turma",
   palette = c("#00AFBB", "#E7B800"),
   ylab = "Densidade")

gghistogram(notas, x = "notas",
   add = "mean", rug = TRUE,
   color = "turma", fill = "turma",
   palette = c("#00AFBB", "#E7B800"))

Using `bins = 30` by default. Pick better value with the argument `bins`.

p <- ggboxplot(notas, x = "turma", y = "notas",
                color = "turma", palette =c("#00AFBB","#FC4E07"),
                add = "jitter", shape = "turma")
p

ggviolin(notas, x = "turma", y = "notas", fill = "turma",
         palette = c("#00AFBB", "#FC4E07"),
         add = "boxplot", add.params = list(fill = "white"))

#ggdotchart(notas, x = "aluno", y = "notas",
#           color = "turma",                                # Color by groups
#           palette = c("#00AFBB", "#FC4E07"), # Custom color palette
#           sorting = "descending",                       # Sort value in descending order
#           add = "segments",                             # Add segments from y = 0 to dots
#           rotate = TRUE,                                # Rotate vertically
#           group = "turma",                                # Order by groups
##           dot.size = 6,                                 # Large dot size
#           label = round(notas$notas),                        # Add mpg values as dot labels
#           font.label = list(color = "white", size = 8, 
#                             vjust = 2.5),               # Adjust label parameters
#           ggtheme = theme_pubr()                        # ggplot2 theme
#           )

#ggdotchart(notas, x = "aluno", y = "notas",
#           color = "turma",                                # Color by groups
#           palette = c("#00AFBB", "#FC4E07"), # Custom color palette
#           sorting = "descending",                       # Sort value in descending order
#           rotate = TRUE,                                # Rotate vertically
#           dot.size = 2,                                 # Large dot size
#           y.text.col = TRUE,                            # Color y text by groups
#           ggtheme = theme_pubr()                        # ggplot2 theme
#           )+
#  theme_cleveland()                                      # Add dashed grids