Atividade 6 - Duas variáveis quantitativas
Eduarda Loureiro
2023-05-18
Introdução
Nessa atividade, realizaremos um diagrama de dispersão de duas variáveis quantitativas e uma matriz de correlação destas mesmas variáveis, na base de dados “FifaData.csv”.
Carregando os pacotes
library(readr)
library(flextable)
library(dplyr)
library(ggplot2)
library(corrplot)Importar do CSV (Coma-Separated Values)
Fifa <- read_delim("C:/Users/eduar/Base_de_dados-master/fifaData.csv")Visualizando os nomes das variáveis
names(Fifa)## [1] "Name" "Nationality" "National_Position"
## [4] "National_Kit" "Club" "Club_Position"
## [7] "Club_Kit" "Club_Joining" "Contract_Expiry"
## [10] "Rating" "Height" "Weight"
## [13] "Preffered_Foot" "Birth_Date" "Age"
## [16] "Preffered_Position" "Work_Rate" "Weak_foot"
## [19] "Skill_Moves" "Ball_Control" "Dribbling"
## [22] "Marking" "Sliding_Tackle" "Standing_Tackle"
## [25] "Aggression" "Reactions" "Attacking_Position"
## [28] "Interceptions" "Vision" "Composure"
## [31] "Crossing" "Short_Pass" "Long_Pass"
## [34] "Acceleration" "Speed" "Stamina"
## [37] "Strength" "Balance" "Agility"
## [40] "Jumping" "Heading" "Shot_Power"
## [43] "Finishing" "Long_Shots" "Curve"
## [46] "Freekick_Accuracy" "Penalties" "Volleys"
## [49] "GK_Positioning" "GK_Diving" "GK_Kicking"
## [52] "GK_Handling" "GK_Reflexes"Classificando as variáveis
class(Fifa$Name)## [1] "character"class(Fifa$Nationality)## [1] "character"class(Fifa$National_Position)## [1] "character"class(Fifa$National_Kit)## [1] "numeric"class(Fifa$Club)## [1] "character"class(Fifa$Club_Position)## [1] "character"class(Fifa$Club_Kit)## [1] "numeric"class(Fifa$Club_Joining)## [1] "character"class(Fifa$Contract_Expiry)## [1] "numeric"class(Fifa$Rating)## [1] "numeric"class(Fifa$Height)## [1] "character"class(Fifa$Weight)## [1] "character"class(Fifa$Preffered_Foot)## [1] "character"class(Fifa$Birth_Date)## [1] "character"class(Fifa$Age)## [1] "numeric"class(Fifa$Preffered_Position)## [1] "character"class(Fifa$Work_Rate)## [1] "character"class(Fifa$Weak_foot)## [1] "numeric"class(Fifa$Skill_Moves)## [1] "numeric"class(Fifa$Ball_Control)## [1] "numeric"class(Fifa$Dribbling)## [1] "numeric"class(Fifa$Marking)## [1] "numeric"class(Fifa$Sliding_Tackle)## [1] "numeric"class(Fifa$Standing_Tackle)## [1] "numeric"class(Fifa$Aggression)## [1] "numeric"class(Fifa$Reactions)## [1] "numeric"class(Fifa$Attacking_Position)## [1] "numeric"class(Fifa$Interceptions)## [1] "numeric"class(Fifa$Vision)## [1] "numeric"class(Fifa$Composure)## [1] "numeric"class(Fifa$Crossing)## [1] "numeric"class(Fifa$Short_Pass)## [1] "numeric"class(Fifa$Long_Pass)## [1] "numeric"class(Fifa$Acceleration)## [1] "numeric"class(Fifa$Speed)## [1] "numeric"class(Fifa$Stamina)## [1] "numeric"class(Fifa$Strength)## [1] "numeric"class(Fifa$Balance)## [1] "numeric"class(Fifa$Agility)## [1] "numeric"class(Fifa$Jumping)## [1] "numeric"class(Fifa$Heading)## [1] "numeric"class(Fifa$Shot_Power)## [1] "numeric"class(Fifa$Finishing)## [1] "numeric"class(Fifa$Long_Shots)## [1] "numeric"class(Fifa$Curve)## [1] "numeric"class(Fifa$Freekick_Accuracy)## [1] "numeric"class(Fifa$Penalties)## [1] "numeric"class(Fifa$Volleys)## [1] "numeric"class(Fifa$GK_Positioning)## [1] "numeric"class(Fifa$GK_Diving)## [1] "numeric"class(Fifa$GK_Kicking)## [1] "numeric"class(Fifa$GK_Handling)## [1] "numeric"class(Fifa$GK_Reflexes)## [1] "numeric"Limpeza de dados
A variável altura aparece nessa base de dados como uma variável qualitativa, mas é quantitativa
Fifa$Height = gsub("cm", "", Fifa$Height)
class(Fifa$Height)## [1] "character"Fifa$Height = as.numeric(Fifa$Height)
class(Fifa$Height)## [1] "numeric"summary(Fifa)## Name Nationality National_Position National_Kit
## Length:17588 Length:17588 Length:17588 Min. : 1.00
## Class :character Class :character Class :character 1st Qu.: 6.00
## Mode :character Mode :character Mode :character Median :12.00
## Mean :12.22
## 3rd Qu.:18.00
## Max. :36.00
## NA's :16513
## Club Club_Position Club_Kit Club_Joining
## Length:17588 Length:17588 Min. : 1.00 Length:17588
## Class :character Class :character 1st Qu.: 9.00 Class :character
## Mode :character Mode :character Median :18.00 Mode :character
## Mean :21.29
## 3rd Qu.:27.00
## Max. :99.00
## NA's :1
## Contract_Expiry Rating Height Weight
## Min. :2017 Min. :45.00 Min. :155.0 Length:17588
## 1st Qu.:2017 1st Qu.:62.00 1st Qu.:176.0 Class :character
## Median :2019 Median :66.00 Median :181.0 Mode :character
## Mean :2019 Mean :66.17 Mean :181.1
## 3rd Qu.:2020 3rd Qu.:71.00 3rd Qu.:186.0
## Max. :2023 Max. :94.00 Max. :207.0
## NA's :1
## Preffered_Foot Birth_Date Age Preffered_Position
## Length:17588 Length:17588 Min. :17.00 Length:17588
## Class :character Class :character 1st Qu.:22.00 Class :character
## Mode :character Mode :character Median :25.00 Mode :character
## Mean :25.46
## 3rd Qu.:29.00
## Max. :47.00
##
## Work_Rate Weak_foot Skill_Moves Ball_Control
## Length:17588 Min. :1.000 Min. :1.000 Min. : 5.00
## Class :character 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:53.00
## Mode :character Median :3.000 Median :2.000 Median :63.00
## Mean :2.934 Mean :2.303 Mean :57.97
## 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:69.00
## Max. :5.000 Max. :5.000 Max. :95.00
##
## Dribbling Marking Sliding_Tackle Standing_Tackle Aggression
## Min. : 4.0 Min. : 3.00 Min. : 5.00 Min. : 3.00 Min. : 2.00
## 1st Qu.:47.0 1st Qu.:22.00 1st Qu.:23.00 1st Qu.:26.00 1st Qu.:44.00
## Median :60.0 Median :48.00 Median :51.00 Median :54.00 Median :59.00
## Mean :54.8 Mean :44.23 Mean :45.57 Mean :47.44 Mean :55.92
## 3rd Qu.:68.0 3rd Qu.:64.00 3rd Qu.:64.00 3rd Qu.:66.00 3rd Qu.:70.00
## Max. :97.0 Max. :92.00 Max. :95.00 Max. :92.00 Max. :96.00
##
## Reactions Attacking_Position Interceptions Vision
## Min. :29.00 Min. : 2.00 Min. : 3.00 Min. :10.00
## 1st Qu.:55.00 1st Qu.:37.00 1st Qu.:26.00 1st Qu.:43.00
## Median :62.00 Median :54.00 Median :52.00 Median :54.00
## Mean :61.77 Mean :49.59 Mean :46.79 Mean :52.71
## 3rd Qu.:68.00 3rd Qu.:64.00 3rd Qu.:64.00 3rd Qu.:64.00
## Max. :96.00 Max. :94.00 Max. :93.00 Max. :94.00
##
## Composure Crossing Short_Pass Long_Pass Acceleration
## Min. : 5.00 Min. : 6.00 Min. :10.00 Min. : 7.0 Min. :11.00
## 1st Qu.:47.00 1st Qu.:38.00 1st Qu.:52.00 1st Qu.:42.0 1st Qu.:57.00
## Median :57.00 Median :54.00 Median :62.00 Median :56.0 Median :68.00
## Mean :55.85 Mean :49.74 Mean :58.12 Mean :52.4 Mean :65.29
## 3rd Qu.:66.00 3rd Qu.:64.00 3rd Qu.:68.00 3rd Qu.:64.0 3rd Qu.:75.00
## Max. :94.00 Max. :91.00 Max. :92.00 Max. :93.0 Max. :96.00
##
## Speed Stamina Strength Balance
## Min. :11.00 Min. :10.00 Min. :20.00 Min. :10.00
## 1st Qu.:58.00 1st Qu.:57.00 1st Qu.:57.00 1st Qu.:56.00
## Median :68.00 Median :66.00 Median :66.00 Median :65.00
## Mean :65.48 Mean :63.48 Mean :65.09 Mean :64.01
## 3rd Qu.:75.00 3rd Qu.:74.00 3rd Qu.:74.00 3rd Qu.:74.00
## Max. :96.00 Max. :95.00 Max. :98.00 Max. :97.00
##
## Agility Jumping Heading Shot_Power
## Min. :11.00 Min. :15.00 Min. : 4.00 Min. : 3.00
## 1st Qu.:55.00 1st Qu.:58.00 1st Qu.:45.00 1st Qu.:45.00
## Median :65.00 Median :65.00 Median :56.00 Median :59.00
## Mean :63.21 Mean :64.92 Mean :52.39 Mean :55.58
## 3rd Qu.:74.00 3rd Qu.:73.00 3rd Qu.:65.00 3rd Qu.:69.00
## Max. :96.00 Max. :95.00 Max. :94.00 Max. :93.00
##
## Finishing Long_Shots Curve Freekick_Accuracy
## Min. : 2.00 Min. : 4.0 Min. : 6.00 Min. : 4.00
## 1st Qu.:29.00 1st Qu.:32.0 1st Qu.:34.00 1st Qu.:31.00
## Median :48.00 Median :52.0 Median :48.00 Median :42.00
## Mean :45.16 Mean :47.4 Mean :47.18 Mean :43.38
## 3rd Qu.:61.00 3rd Qu.:63.0 3rd Qu.:62.00 3rd Qu.:57.00
## Max. :95.00 Max. :91.0 Max. :92.00 Max. :93.00
##
## Penalties Volleys GK_Positioning GK_Diving
## Min. : 7.00 Min. : 3.00 Min. : 1.00 Min. : 1.00
## 1st Qu.:39.00 1st Qu.:30.00 1st Qu.: 8.00 1st Qu.: 8.00
## Median :50.00 Median :44.00 Median :11.00 Median :11.00
## Mean :49.17 Mean :43.28 Mean :16.61 Mean :16.82
## 3rd Qu.:61.00 3rd Qu.:57.00 3rd Qu.:14.00 3rd Qu.:14.00
## Max. :96.00 Max. :93.00 Max. :91.00 Max. :89.00
##
## GK_Kicking GK_Handling GK_Reflexes
## Min. : 1.00 Min. : 1.00 Min. : 1.0
## 1st Qu.: 8.00 1st Qu.: 8.00 1st Qu.: 8.0
## Median :11.00 Median :11.00 Median :11.0
## Mean :16.46 Mean :16.56 Mean :16.9
## 3rd Qu.:14.00 3rd Qu.:14.00 3rd Qu.:14.0
## Max. :95.00 Max. :91.00 Max. :90.0
## Problema resolvido.
Resumo da base de dados
summary(Fifa)## Name Nationality National_Position National_Kit
## Length:17588 Length:17588 Length:17588 Min. : 1.00
## Class :character Class :character Class :character 1st Qu.: 6.00
## Mode :character Mode :character Mode :character Median :12.00
## Mean :12.22
## 3rd Qu.:18.00
## Max. :36.00
## NA's :16513
## Club Club_Position Club_Kit Club_Joining
## Length:17588 Length:17588 Min. : 1.00 Length:17588
## Class :character Class :character 1st Qu.: 9.00 Class :character
## Mode :character Mode :character Median :18.00 Mode :character
## Mean :21.29
## 3rd Qu.:27.00
## Max. :99.00
## NA's :1
## Contract_Expiry Rating Height Weight
## Min. :2017 Min. :45.00 Min. :155.0 Length:17588
## 1st Qu.:2017 1st Qu.:62.00 1st Qu.:176.0 Class :character
## Median :2019 Median :66.00 Median :181.0 Mode :character
## Mean :2019 Mean :66.17 Mean :181.1
## 3rd Qu.:2020 3rd Qu.:71.00 3rd Qu.:186.0
## Max. :2023 Max. :94.00 Max. :207.0
## NA's :1
## Preffered_Foot Birth_Date Age Preffered_Position
## Length:17588 Length:17588 Min. :17.00 Length:17588
## Class :character Class :character 1st Qu.:22.00 Class :character
## Mode :character Mode :character Median :25.00 Mode :character
## Mean :25.46
## 3rd Qu.:29.00
## Max. :47.00
##
## Work_Rate Weak_foot Skill_Moves Ball_Control
## Length:17588 Min. :1.000 Min. :1.000 Min. : 5.00
## Class :character 1st Qu.:3.000 1st Qu.:2.000 1st Qu.:53.00
## Mode :character Median :3.000 Median :2.000 Median :63.00
## Mean :2.934 Mean :2.303 Mean :57.97
## 3rd Qu.:3.000 3rd Qu.:3.000 3rd Qu.:69.00
## Max. :5.000 Max. :5.000 Max. :95.00
##
## Dribbling Marking Sliding_Tackle Standing_Tackle Aggression
## Min. : 4.0 Min. : 3.00 Min. : 5.00 Min. : 3.00 Min. : 2.00
## 1st Qu.:47.0 1st Qu.:22.00 1st Qu.:23.00 1st Qu.:26.00 1st Qu.:44.00
## Median :60.0 Median :48.00 Median :51.00 Median :54.00 Median :59.00
## Mean :54.8 Mean :44.23 Mean :45.57 Mean :47.44 Mean :55.92
## 3rd Qu.:68.0 3rd Qu.:64.00 3rd Qu.:64.00 3rd Qu.:66.00 3rd Qu.:70.00
## Max. :97.0 Max. :92.00 Max. :95.00 Max. :92.00 Max. :96.00
##
## Reactions Attacking_Position Interceptions Vision
## Min. :29.00 Min. : 2.00 Min. : 3.00 Min. :10.00
## 1st Qu.:55.00 1st Qu.:37.00 1st Qu.:26.00 1st Qu.:43.00
## Median :62.00 Median :54.00 Median :52.00 Median :54.00
## Mean :61.77 Mean :49.59 Mean :46.79 Mean :52.71
## 3rd Qu.:68.00 3rd Qu.:64.00 3rd Qu.:64.00 3rd Qu.:64.00
## Max. :96.00 Max. :94.00 Max. :93.00 Max. :94.00
##
## Composure Crossing Short_Pass Long_Pass Acceleration
## Min. : 5.00 Min. : 6.00 Min. :10.00 Min. : 7.0 Min. :11.00
## 1st Qu.:47.00 1st Qu.:38.00 1st Qu.:52.00 1st Qu.:42.0 1st Qu.:57.00
## Median :57.00 Median :54.00 Median :62.00 Median :56.0 Median :68.00
## Mean :55.85 Mean :49.74 Mean :58.12 Mean :52.4 Mean :65.29
## 3rd Qu.:66.00 3rd Qu.:64.00 3rd Qu.:68.00 3rd Qu.:64.0 3rd Qu.:75.00
## Max. :94.00 Max. :91.00 Max. :92.00 Max. :93.0 Max. :96.00
##
## Speed Stamina Strength Balance
## Min. :11.00 Min. :10.00 Min. :20.00 Min. :10.00
## 1st Qu.:58.00 1st Qu.:57.00 1st Qu.:57.00 1st Qu.:56.00
## Median :68.00 Median :66.00 Median :66.00 Median :65.00
## Mean :65.48 Mean :63.48 Mean :65.09 Mean :64.01
## 3rd Qu.:75.00 3rd Qu.:74.00 3rd Qu.:74.00 3rd Qu.:74.00
## Max. :96.00 Max. :95.00 Max. :98.00 Max. :97.00
##
## Agility Jumping Heading Shot_Power
## Min. :11.00 Min. :15.00 Min. : 4.00 Min. : 3.00
## 1st Qu.:55.00 1st Qu.:58.00 1st Qu.:45.00 1st Qu.:45.00
## Median :65.00 Median :65.00 Median :56.00 Median :59.00
## Mean :63.21 Mean :64.92 Mean :52.39 Mean :55.58
## 3rd Qu.:74.00 3rd Qu.:73.00 3rd Qu.:65.00 3rd Qu.:69.00
## Max. :96.00 Max. :95.00 Max. :94.00 Max. :93.00
##
## Finishing Long_Shots Curve Freekick_Accuracy
## Min. : 2.00 Min. : 4.0 Min. : 6.00 Min. : 4.00
## 1st Qu.:29.00 1st Qu.:32.0 1st Qu.:34.00 1st Qu.:31.00
## Median :48.00 Median :52.0 Median :48.00 Median :42.00
## Mean :45.16 Mean :47.4 Mean :47.18 Mean :43.38
## 3rd Qu.:61.00 3rd Qu.:63.0 3rd Qu.:62.00 3rd Qu.:57.00
## Max. :95.00 Max. :91.0 Max. :92.00 Max. :93.00
##
## Penalties Volleys GK_Positioning GK_Diving
## Min. : 7.00 Min. : 3.00 Min. : 1.00 Min. : 1.00
## 1st Qu.:39.00 1st Qu.:30.00 1st Qu.: 8.00 1st Qu.: 8.00
## Median :50.00 Median :44.00 Median :11.00 Median :11.00
## Mean :49.17 Mean :43.28 Mean :16.61 Mean :16.82
## 3rd Qu.:61.00 3rd Qu.:57.00 3rd Qu.:14.00 3rd Qu.:14.00
## Max. :96.00 Max. :93.00 Max. :91.00 Max. :89.00
##
## GK_Kicking GK_Handling GK_Reflexes
## Min. : 1.00 Min. : 1.00 Min. : 1.0
## 1st Qu.: 8.00 1st Qu.: 8.00 1st Qu.: 8.0
## Median :11.00 Median :11.00 Median :11.0
## Mean :16.46 Mean :16.56 Mean :16.9
## 3rd Qu.:14.00 3rd Qu.:14.00 3rd Qu.:14.0
## Max. :95.00 Max. :91.00 Max. :90.0
## Hipóteses
1.Jogadores mais novos são mais velozes (age + speed) 2.Jogadores mais altos correm mais (height + speed) 3.Jogadores mais novos são mais agressivos (age + aggression)
Realizando a correlação e o diagrama de dispersão para responder as hipóteses
Hipótese 1 - Jogadores mais novos são mais velozes
plot(Fifa$Age, Fifa$Speed,
col="blue",
pch=19,
main = "Diagrama de dispersão",
xlab = "Idade dos jogadores",
ylab = "Velocidade dos jogadores")
abline(lsfit(Fifa$Age, Fifa$Speed), col="red")
cor(Fifa$Age, Fifa$Speed)## [1] -0.1684175A correlação entre a idade dos jogadores e sua velocidade foi de -0.1684175 É uma correlação negativa e fraca.
Então podemos analisar que a idade dos jogadores tem pouca influencia em sua velocidade, mas pode ser algo que interfere bastante no desempenho deles.
Um jogador mais novo consegue ter uma velocidade maior, mas os mais velhos não ficam muito para trás. Então essa hipótese
Hipótese 2 - Jogadores mais altos correm mais
plot(Fifa$Height, Fifa$Speed,
col="green",
pch=19,
main = "Diagrama de dispersão",
xlab = "Altura dos jogadores",
ylab = "Velocidade dos jogadores")
abline(lsfit(Fifa$Height, Fifa$Speed), col="red")
cor(Fifa$Height, Fifa$Speed)## [1] -0.4511171A correlação entre a altura dos jogadores e a sua velocidade é de -0.4511171.
É uma correlação negativa e forte.
Então podemos analisar que há uma influência, mas não há uma interferência tão grande.
Mesmo se um jogador for o mais alto, não necessariamente ele será o mais veloz como é possível perceber no diagrama de dispersão.
Hipótese 3 - Jogadores mais novos são mais agressivos
plot(Fifa$Age, Fifa$Aggression,
col="yellow",
pch=19,
main = "Diagrama de dispersão",
xlab = "Idade dos jogadores",
ylab = "Agressividade dos jogadores")
abline(lsfit(Fifa$Age, Fifa$Aggression), col="red")
cor(Fifa$Age, Fifa$Aggression)## [1] 0.2595643A correlação entre a idade e a agressão dos jogadores é de 0.2595643.
É uma correlação positiva e forte.
Podemos analisar nesse diagrama de dispersão que quanto mais velho o jogador, menos agressivo tende a ser, então a hipótese está confirmada: jogadores mais novos tendem a ser mais agressivos.
Correlação de todas as variáveis
Fifa %>% select(Age,Speed, Height, Aggression) %>% cor() %>% corrplot.mixed()
Conseguimos por fim analisar que a maior correlação foi entre a velocidade dos jogadores e sua altura, podendo confirmar que não é porque um jogador é o mais alto que ele necessariamente é o mais veloz.
Conclusão
Nessa atividade foi possível responder hipóteses geradas de forma clara, onde pudemos constatar a correlação e a dispersão das informações sobre os jogadores que são importantes para o futuro deles e de seus clubes.