Latihan

ANALisis data celfit

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library(car)

## Warning: package 'car' was built under R version 4.1.3

## Loading required package: carData

## Warning: package 'carData' was built under R version 4.1.3

DataMember <- read.csv("Data Fitnes.csv")
DataMember$grpMetode <- cut(DataMember$Metode,
                            breaks = c(0, 1, 2, 3, Inf),
                            labels = c("Mod-1","Mod-2","Mod-3","Mod-4"))

DataMember$grpUmur <- cut(DataMember$Metode,
                          breaks = c(0, 1, 2, Inf),
                          labels = c("<20","20-40",">40"))    


# data diperoleh pada tanggal 21 juni 2022

head(DataMember)

##                 MemberName Berat Metode Umur grpMetode grpUmur
## 1        NUR MEI CHASANATI     5      1    1     Mod-1     <20
## 2                 SUPRAPTO     4      1    1     Mod-1     <20
## 3             TITI PRIYONO     5      1    1     Mod-1     <20
## 4                   SUSENO     5      1    2     Mod-1     <20
## 5              ALIP ASMADI     6      1    2     Mod-1     <20
## 6 IRAWAN EKOBOEDJO MARGONO     2      1    2     Mod-1     <20

AnovaModel1Arah <- lm(data = DataMember,
                            formula = Berat~grpUmur)
anova(AnovaModel1Arah)

## Analysis of Variance Table
## 
## Response: Berat
##           Df Sum Sq Mean Sq F value  Pr(>F)  
## grpUmur    2 22.222 11.1111    3.91 0.02993 *
## Residuals 33 93.778  2.8418                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

AnovaModel2Arah <- lm(data = DataMember,
                      formula = Berat~grpUmur+grpMetode)
anova(AnovaModel2Arah)

## Analysis of Variance Table
## 
## Response: Berat
##           Df Sum Sq Mean Sq F value  Pr(>F)  
## grpUmur    2 22.222 11.1111  3.8278 0.03233 *
## grpMetode  1  0.889  0.8889  0.3062 0.58385  
## Residuals 32 92.889  2.9028                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1