Diagrama de dispersão

coeficiente de correlação

CARREGAR BASE DE DADOS

library(readr)
FifaData <- read_csv("C:/Users/ziin/Documents/FACULDADE/estatistica/FifaData.csv")
## 
## -- Column specification --------------------------------------------------------
## cols(
##   .default = col_double(),
##   Name = col_character(),
##   Nationality = col_character(),
##   National_Position = col_character(),
##   Club = col_character(),
##   Club_Position = col_character(),
##   Club_Joining = col_character(),
##   Height = col_character(),
##   Weight = col_character(),
##   Preffered_Foot = col_character(),
##   Birth_Date = col_character(),
##   Preffered_Position = col_character(),
##   Work_Rate = col_character()
## )
## i Use `spec()` for the full column specifications.
View(FifaData)
names(FifaData)
##  [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"

DISPERSÃO

DIAGRAMA DE DISPERSÃO

CORRELAÇÕES

CORRELAÇÕES ENTRE SPEED(RAPIDEZ) E MARKING (MARCAÇÃO)

cor(FifaData$Speed,FifaData$Marking)
## [1] 0.1632428
## 
## 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
##  [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"
##             Speed   Marking
## Speed   1.0000000 0.1632428
## Marking 0.1632428 1.0000000
library(corrplot)
## Warning: package 'corrplot' was built under R version 4.0.5
## corrplot 0.84 loaded
MCorr <- cor(FifaData_quanti)
corrplot(MCorr,addCoef.col=TRUE,number.cex=0.7)

CONCLUSÃO

Como o Diagrama de Dispersão e a correlação, analisaremos a relação e a intensidade em que ocorre, entre as variáveis : Speed(Rapidez) e Marking(Marcação).

Podemos observar que, a correlação entre as variáveis é positiva e fraca,pois o valor da correlação está em torno de 0,1, mas não deixa de ser positiva , pois, os pontos tendem a crescer simultaneamente e próximos um dos outros.