Aula 5 - QUALITATIVA X QUANTITATIVA

Carregando pacotes necessarios

library(readxl)
library(flextable)
## Warning: package 'flextable' was built under R version 4.2.3
library(dplyr)
## Warning: package 'dplyr' was built under R version 4.2.3
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(ggplot2)
## Warning: package 'ggplot2' was built under R version 4.2.3

Importando a base de dados

QE = read_excel("C:/Users/eduar/Base_de_dados-master/Questionario_Estresse.xls",
                sheet = "Dados")
names(QE)
##  [1] "Aluno"        "Turma"        "Mora_pais"    "RJ"           "Namorado_a"  
##  [6] "Trabalha"     "Desempenho"   "Estresse"     "Créditos"     "Horas_estudo"
colnames(QE)[9] = 'Creditos'

Mostrar a base de dados

head(QE) %>% flextable() %>% theme_tron_legacy()

Aluno

Turma

Mora_pais

RJ

Namorado_a

Trabalha

Desempenho

Estresse

Creditos

Horas_estudo

1

1

2

2

2

2

8.89

23

27

27

2

1

1

1

2

2

8.80

24

28

28

3

1

2

2

2

2

8.00

25

25

25

4

1

2

2

1

1

8.80

38

21

30

5

1

2

2

2

1

8.90

41

18

20

6

1

2

2

1

1

8.10

25

29

32

Limpeza dos dados

QE$Mora_pais = ifelse(QE$Mora_pais==1, "Sim", "Nao")
QE$RJ = ifelse(QE$RJ==1, "Sim", "Nao")
QE$Trabalha = ifelse(QE$Trabalha==1, "Sim", "Nao")
QE$Namorado_a = ifelse(QE$Namorado_a==1, "Sim", "Nao")

QE\(TURMA = as.factor(QE\)Turma)

QE$Turma = ifelse(QE$Turma==1, "Turma1", ifelse(QE$Turma==2, "Turma2",
                                                "Turma3"))
# Hipoteses
# Hipotese 1 - Quem trabalha estuda menos? # Hipotese 2 - Quem mora sozinho é mais estressado? # Hipotese 3 - Quem namora tem uma nota menor? # Hipotese 4 - A turma 1 é tem um desempenho melhor que a turma 2 e 3?
# Operacionalizar # Variaveis resposta: Horas de estudo, Estresse, Desempenho # Variaveis explicativas: Trabalha, Mora com os pais, Namora, Turma
# Media e desvio padrao
r QE %>% select(Trabalha, Horas_estudo) %>% group_by(Trabalha) %>% summarise(media=mean(Horas_estudo), desvio_padrao=sd(Horas_estudo)) %>% flextable()
{=html} <div class="tabwid"><style>.cl-c64f174e{}.cl-c63acb68{font-family:'Arial';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-c642293a{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c6422944{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c64251b2{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c64251c6{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c64251c7{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c64251d0{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c64251d1{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c64251da{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing='true' class='cl-c64f174e'><thead><tr style="overflow-wrap:break-word;"><th class="cl-c64251b2"><p class="cl-c642293a"><span class="cl-c63acb68">Trabalha</span></p></th><th class="cl-c64251c6"><p class="cl-c6422944"><span class="cl-c63acb68">media</span></p></th><th class="cl-c64251c6"><p class="cl-c6422944"><span class="cl-c63acb68">desvio_padrao</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-c64251c7"><p class="cl-c642293a"><span class="cl-c63acb68">Nao</span></p></td><td class="cl-c64251d0"><p class="cl-c6422944"><span class="cl-c63acb68">31.55932</span></p></td><td class="cl-c64251d0"><p class="cl-c6422944"><span class="cl-c63acb68">6.928878</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-c64251d1"><p class="cl-c642293a"><span class="cl-c63acb68">Sim</span></p></td><td class="cl-c64251da"><p class="cl-c6422944"><span class="cl-c63acb68">29.36111</span></p></td><td class="cl-c64251da"><p class="cl-c6422944"><span class="cl-c63acb68">7.716967</span></p></td></tr></tbody></table></div> o valor medio de quem nao trabalha é 31 e quem trabalha é 29
# Minimo, 1 quartil, mediana 2 quartil, maximo 3 quartil
r QE %>% select(Trabalha, Horas_estudo) %>% group_by(Trabalha) %>% summarise(minimo=min(Horas_estudo), quartil1 = quantile(Horas_estudo, 0.25), mediana = median(Horas_estudo), quartil3 = quantile(Horas_estudo, 0.75), maximo = max(Horas_estudo)) %>% flextable()
{=html} <div class="tabwid"><style>.cl-c6934478{}.cl-c680904e{font-family:'Arial';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(0, 0, 0, 1.00);background-color:transparent;}.cl-c6876752{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c6876766{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c6878f48{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6878f52{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 1.5pt solid rgba(102, 102, 102, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6878f5c{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6878f5d{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6878f66{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6878f67{width:0.75in;background-color:transparent;vertical-align: middle;border-bottom: 1.5pt solid rgba(102, 102, 102, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing='true' class='cl-c6934478'><thead><tr style="overflow-wrap:break-word;"><th class="cl-c6878f48"><p class="cl-c6876752"><span class="cl-c680904e">Trabalha</span></p></th><th class="cl-c6878f52"><p class="cl-c6876766"><span class="cl-c680904e">minimo</span></p></th><th class="cl-c6878f52"><p class="cl-c6876766"><span class="cl-c680904e">quartil1</span></p></th><th class="cl-c6878f52"><p class="cl-c6876766"><span class="cl-c680904e">mediana</span></p></th><th class="cl-c6878f52"><p class="cl-c6876766"><span class="cl-c680904e">quartil3</span></p></th><th class="cl-c6878f52"><p class="cl-c6876766"><span class="cl-c680904e">maximo</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-c6878f5c"><p class="cl-c6876752"><span class="cl-c680904e">Nao</span></p></td><td class="cl-c6878f5d"><p class="cl-c6876766"><span class="cl-c680904e">20</span></p></td><td class="cl-c6878f5d"><p class="cl-c6876766"><span class="cl-c680904e">28.00</span></p></td><td class="cl-c6878f5d"><p class="cl-c6876766"><span class="cl-c680904e">30</span></p></td><td class="cl-c6878f5d"><p class="cl-c6876766"><span class="cl-c680904e">35.0</span></p></td><td class="cl-c6878f5d"><p class="cl-c6876766"><span class="cl-c680904e">60</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-c6878f66"><p class="cl-c6876752"><span class="cl-c680904e">Sim</span></p></td><td class="cl-c6878f67"><p class="cl-c6876766"><span class="cl-c680904e">19</span></p></td><td class="cl-c6878f67"><p class="cl-c6876766"><span class="cl-c680904e">24.75</span></p></td><td class="cl-c6878f67"><p class="cl-c6876766"><span class="cl-c680904e">30</span></p></td><td class="cl-c6878f67"><p class="cl-c6876766"><span class="cl-c680904e">33.5</span></p></td><td class="cl-c6878f67"><p class="cl-c6876766"><span class="cl-c680904e">59</span></p></td></tr></tbody></table></div>
r QE %>% select(Mora_pais, Estresse) %>% group_by(Mora_pais) %>% summarise(media=mean(Estresse), desvio_padrao = sd(Estresse)) %>% flextable() %>% theme_vader()
{=html} <div class="tabwid"><style>.cl-c6d0c0f0{}.cl-c6bf91cc{font-family:'Arial';font-size:11pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(223, 223, 223, 1.00);background-color:transparent;}.cl-c6bf91e0{font-family:'Arial';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(223, 223, 223, 1.00);background-color:transparent;}.cl-c6c77108{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c6c77112{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c6c790de{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(255, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6c790e8{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(255, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6c790e9{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c6c790f2{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing='true' class='cl-c6d0c0f0'><thead><tr style="overflow-wrap:break-word;"><th class="cl-c6c790de"><p class="cl-c6c77108"><span class="cl-c6bf91cc">Mora_pais</span></p></th><th class="cl-c6c790e8"><p class="cl-c6c77112"><span class="cl-c6bf91cc">media</span></p></th><th class="cl-c6c790e8"><p class="cl-c6c77112"><span class="cl-c6bf91cc">desvio_padrao</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-c6c790e9"><p class="cl-c6c77108"><span class="cl-c6bf91e0">Nao</span></p></td><td class="cl-c6c790f2"><p class="cl-c6c77112"><span class="cl-c6bf91e0">27.56863</span></p></td><td class="cl-c6c790f2"><p class="cl-c6c77112"><span class="cl-c6bf91e0">7.915188</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-c6c790e9"><p class="cl-c6c77108"><span class="cl-c6bf91e0">Sim</span></p></td><td class="cl-c6c790f2"><p class="cl-c6c77112"><span class="cl-c6bf91e0">28.11364</span></p></td><td class="cl-c6c790f2"><p class="cl-c6c77112"><span class="cl-c6bf91e0">7.160018</span></p></td></tr></tbody></table></div>
r QE %>% select(Namorado_a, Desempenho) %>% group_by(Namorado_a) %>% summarise(media=mean(Desempenho), desvio_padrao = sd(Desempenho)) %>% flextable() %>% theme_vader()
{=html} <div class="tabwid"><style>.cl-c70dbc8a{}.cl-c6fb96ae{font-family:'Arial';font-size:11pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(223, 223, 223, 1.00);background-color:transparent;}.cl-c6fb96cc{font-family:'Arial';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(223, 223, 223, 1.00);background-color:transparent;}.cl-c702d07c{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c702d086{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c702f840{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(255, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c702f854{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(255, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c702f85e{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c702f868{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing='true' class='cl-c70dbc8a'><thead><tr style="overflow-wrap:break-word;"><th class="cl-c702f840"><p class="cl-c702d07c"><span class="cl-c6fb96ae">Namorado_a</span></p></th><th class="cl-c702f854"><p class="cl-c702d086"><span class="cl-c6fb96ae">media</span></p></th><th class="cl-c702f854"><p class="cl-c702d086"><span class="cl-c6fb96ae">desvio_padrao</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-c702f85e"><p class="cl-c702d07c"><span class="cl-c6fb96cc">Nao</span></p></td><td class="cl-c702f868"><p class="cl-c702d086"><span class="cl-c6fb96cc">8.437917</span></p></td><td class="cl-c702f868"><p class="cl-c702d086"><span class="cl-c6fb96cc">0.7373557</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-c702f85e"><p class="cl-c702d07c"><span class="cl-c6fb96cc">Sim</span></p></td><td class="cl-c702f868"><p class="cl-c702d086"><span class="cl-c6fb96cc">8.752979</span></p></td><td class="cl-c702f868"><p class="cl-c702d086"><span class="cl-c6fb96cc">0.7884269</span></p></td></tr></tbody></table></div>
r QE %>% select(Turma, Desempenho) %>% group_by(Turma) %>% summarise(media=mean(Desempenho), desvio_padrao = sd(Desempenho)) %>% flextable() %>% theme_vader()
{=html} <div class="tabwid"><style>.cl-c74a7bf2{}.cl-c737b666{font-family:'Arial';font-size:11pt;font-weight:bold;font-style:normal;text-decoration:none;color:rgba(223, 223, 223, 1.00);background-color:transparent;}.cl-c737b684{font-family:'Arial';font-size:11pt;font-weight:normal;font-style:normal;text-decoration:none;color:rgba(223, 223, 223, 1.00);background-color:transparent;}.cl-c73f5736{margin:0;text-align:left;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c73f574a{margin:0;text-align:right;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);padding-bottom:5pt;padding-top:5pt;padding-left:5pt;padding-right:5pt;line-height: 1;background-color:transparent;}.cl-c73f827e{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(255, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c73f8292{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 1.5pt solid rgba(255, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c73f829c{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}.cl-c73f829d{width:0.75in;background-color:rgba(36, 36, 36, 1.00);vertical-align: middle;border-bottom: 0 solid rgba(0, 0, 0, 1.00);border-top: 0 solid rgba(0, 0, 0, 1.00);border-left: 0 solid rgba(0, 0, 0, 1.00);border-right: 0 solid rgba(0, 0, 0, 1.00);margin-bottom:0;margin-top:0;margin-left:0;margin-right:0;}</style><table data-quarto-disable-processing='true' class='cl-c74a7bf2'><thead><tr style="overflow-wrap:break-word;"><th class="cl-c73f827e"><p class="cl-c73f5736"><span class="cl-c737b666">Turma</span></p></th><th class="cl-c73f8292"><p class="cl-c73f574a"><span class="cl-c737b666">media</span></p></th><th class="cl-c73f8292"><p class="cl-c73f574a"><span class="cl-c737b666">desvio_padrao</span></p></th></tr></thead><tbody><tr style="overflow-wrap:break-word;"><td class="cl-c73f829c"><p class="cl-c73f5736"><span class="cl-c737b684">Turma1</span></p></td><td class="cl-c73f829d"><p class="cl-c73f574a"><span class="cl-c737b684">8.610357</span></p></td><td class="cl-c73f829d"><p class="cl-c73f574a"><span class="cl-c737b684">0.4413320</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-c73f829c"><p class="cl-c73f5736"><span class="cl-c737b684">Turma2</span></p></td><td class="cl-c73f829d"><p class="cl-c73f574a"><span class="cl-c737b684">8.710000</span></p></td><td class="cl-c73f829d"><p class="cl-c73f574a"><span class="cl-c737b684">0.6627509</span></p></td></tr><tr style="overflow-wrap:break-word;"><td class="cl-c73f829c"><p class="cl-c73f5736"><span class="cl-c737b684">Turma3</span></p></td><td class="cl-c73f829d"><p class="cl-c73f574a"><span class="cl-c737b684">8.474286</span></p></td><td class="cl-c73f829d"><p class="cl-c73f574a"><span class="cl-c737b684">1.0388095</span></p></td></tr></tbody></table></div>
r boxplot(QE$Desempenho ~ QE$Turma, col=c("red", "blue", "yellow"), main="Gráfico1 - Boxplot da nota por turma", ylab = "Nota da prova", xlab = "Turma")
Turma 1 ta concentrada bolinhas no 3- outliers (mt gnt fora da curva) o tamanho da caixa representa o desvio padrao turma 3 maior diversidade turma 1 é a maior concentrada
r boxplot(QE$Horas_estudo ~ QE$Trabalha, col=c("green", "pink"), main="Gráfico2 - Boxplot quem trabalha e estuda", ylab = "Horas de estudo", xlab = "Trabalha")
# Graficos
r QE %>% ggplot(aes(x=Trabalha, y=Horas_estudo)) + geom_boxplot(fill="red") + labs(title = "boxplot", subtitle = "das horas de estudo por trabalho", caption = "Fonte: Base questionario estresse. Processamento: loureiroduda") + theme_minimal()
r library(ggridges)
## Warning: package 'ggridges' was built under R version 4.2.3
r QE %>% select(Turma, Horas_estudo) %>% ggplot() + geom_density_ridges(aes(x = Horas_estudo, y = Turma, group = Turma, fill = Turma)) + theme_minimal()
## Picking joint bandwidth of 2.59

Trabalhando com outra base de dados para criação de mapas

library(readxl)
BasesEstados <- read_excel("~/Estatistica 2023 UNIRIO/Base_de_dados-master/BasesEstados.xlsx")
View(BasesEstados)

Variaveis de interesse IDH, População e Renda per capita

library(geobr)
## Warning: package 'geobr' was built under R version 4.2.3
## Loading required namespace: sf
mapa = geobr::read_state()
## Using year 2010
## 
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names(BasesEstados)
##  [1] "S"                            "Sigla"                       
##  [3] "Codigo"                       "Estado"                      
##  [5] "Região"                       "CodigoReg"                   
##  [7] "PIB"                          "Gini"                        
##  [9] "Agua"                         "Banheiro"                    
## [11] "Lixo"                         "Energia"                     
## [13] "Densidade"                    "Esperancadevida"             
## [15] "Populacao"                    "Mortalidade_infantil"        
## [17] "Prob_sobrevivencia"           "IDH"                         
## [19] "IDH_Renda"                    "IDH_Longevidade"             
## [21] "IDH_Educacao"                 "Probab_sobrev60"             
## [23] "TFT"                          "Taxa_envelhecimento"         
## [25] "Taxa_analfabetismo"           "frequencia_liquida_EM"       
## [27] "Expectativa_anos_de_estudo"   "frequencia_liquida_Superior" 
## [29] "perc_com_2_anos_de_de_atraso" "Renda_per_capita"            
## [31] "Renda_per_capita_nula"        "Perc_pobres"                 
## [33] "Perc_extremamente_pobres"     "Despesa_Corrente"            
## [35] "Despesa_Corrente_per_capita"
names(mapa)
## [1] "code_state"   "abbrev_state" "name_state"   "code_region"  "name_region" 
## [6] "geom"
library(dplyr)
BasesEstados = BasesEstados %>% rename(code_state=Codigo)
class(mapa$code_state)
## [1] "numeric"
class(BasesEstados$code_state)
## [1] "character"
BasesEstados$code_state = as.numeric(BasesEstados$code_state)
dados_mais_mapa = mapa %>% left_join(BasesEstados)
## Joining with `by = join_by(code_state)`
library(ggplot2)
dados_mais_mapa %>% ggplot() +
  geom_sf(data=dados_mais_mapa, aes(fill=IDH)) +
  theme_minimal()

quanto mais claro, mais gente em notação científica

dados_mais_mapa %>% ggplot() +
  geom_sf(data=dados_mais_mapa, 
          aes(fill=Populacao)) +
  scale_fill_distiller(palette = "Reds",
                       direction = 1, name="População") + 
  theme_minimal()

dados_mais_mapa %>% ggplot() +
  geom_sf(aes(fill=Renda_per_capita)) +
  scale_fill_distiller(palette = "Purples",
                       direction = 1, 
                       name="População") + 
  theme_minimal()

dados_mais_mapa %>% ggplot() +
  geom_sf(aes(fill=Mortalidade_infantil)) +
  scale_fill_distiller(palette = "Spectral",
                       direction = 1, 
                       name="População") + 
  theme_minimal()

 library(RColorBrewer)
display.brewer.all()