Hasil Analisis Data Fitnes Menggunakan ANOVA

Data member fitnes Buitenzorg telah diperoleh pada tanggal 22 Januari 2022 dengan susunan sebagai berikut

library(car) # Supaya bisa execute fungsi "Anova()"
## Loading required package: carData
DataMember <- read.csv("Data Fitnes.csv")

# Membuat kelompok; Metode dan Umur
DataMember$grpMetode <- cut(DataMember$Metode,
                            breaks = c(0, 1, 2, 3, Inf),
                            labels = c("Mod-1","Mod-2","Mod-3","Mod-4"))

DataMember$grpUmur <- cut(DataMember$Umur,
                          breaks = c(0, 1, 2, Inf),
                          labels = c("<20","20-40",">40"))
# Melihat korelasi antara perubahan berat badan dengan umur
cor.test(DataMember$Berat, DataMember$Metode)
## 
##  Pearson's product-moment correlation
## 
## data:  DataMember$Berat and DataMember$Metode
## t = -0.64964, df = 34, p-value = 0.5203
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.4238445  0.2260310
## sample estimates:
##        cor 
## -0.1107273
# Mengukur pengaruh antara umur terhadap penambahan berat badan
AnovaModel1Arah <- lm(data = DataMember,
                      formula = Berat~grpUmur)
Anova(AnovaModel1Arah)
## Anova Table (Type II tests)
## 
## Response: Berat
##            Sum Sq Df F value Pr(>F)
## grpUmur     0.667  2  0.0954 0.9093
## Residuals 115.333 33
# Mengukur pengaruh antara umur dan meotde terhadap berat badan
AnovaModel2Arah <- lm(data = DataMember,
                      formula = Berat~grpMetode*grpUmur)
Anova(AnovaModel2Arah)
## Anova Table (Type II tests)
## 
## Response: Berat
##                   Sum Sq Df F value  Pr(>F)  
## grpMetode         23.111  3  3.0476 0.04811 *
## grpUmur            0.667  2  0.1319 0.87709  
## grpMetode:grpUmur 31.556  6  2.0806 0.09350 .
## Residuals         60.667 24                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
AnovaModel1AOV <- lm(data = DataMember,
                     formula = Berat~grpMetode+grpUmur)
Anova(AnovaModel1AOV)
## Anova Table (Type II tests)
## 
## Response: Berat
##           Sum Sq Df F value  Pr(>F)  
## grpMetode 23.111  3  2.5060 0.07797 .
## grpUmur    0.667  2  0.1084 0.89759  
## Residuals 92.222 30                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
summary(AnovaModel2Arah)
## 
## Call:
## lm(formula = Berat ~ grpMetode * grpUmur, data = DataMember)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.3333 -0.6667 -0.3333  1.0833  3.0000 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   4.6667     0.9179   5.084 3.36e-05 ***
## grpMetodeMod-2               -3.6667     1.2981  -2.825  0.00938 ** 
## grpMetodeMod-3                0.3333     1.2981   0.257  0.79954    
## grpMetodeMod-4               -2.0000     1.2981  -1.541  0.13648    
## grpUmur20-40                 -0.3333     1.2981  -0.257  0.79954    
## grpUmur>40                   -0.3333     1.2981  -0.257  0.79954    
## grpMetodeMod-2:grpUmur20-40   1.6667     1.8359   0.908  0.37299    
## grpMetodeMod-3:grpUmur20-40  -2.0000     1.8359  -1.089  0.28679    
## grpMetodeMod-4:grpUmur20-40   1.0000     1.8359   0.545  0.59098    
## grpMetodeMod-2:grpUmur>40     2.6667     1.8359   1.453  0.15930    
## grpMetodeMod-3:grpUmur>40    -3.0000     1.8359  -1.634  0.11529    
## grpMetodeMod-4:grpUmur>40     2.3333     1.8359   1.271  0.21592    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.59 on 24 degrees of freedom
## Multiple R-squared:  0.477,  Adjusted R-squared:  0.2373 
## F-statistic:  1.99 on 11 and 24 DF,  p-value: 0.07694
summary(AnovaModel1AOV)
## 
## Call:
## lm(formula = Berat ~ grpMetode + grpUmur, data = DataMember)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -2.3889 -1.2361 -0.1667  0.7639  4.8889 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)    
## (Intercept)      4.4444     0.7158   6.209 7.78e-07 ***
## grpMetodeMod-2  -2.2222     0.8265  -2.689   0.0116 *  
## grpMetodeMod-3  -1.3333     0.8265  -1.613   0.1172    
## grpMetodeMod-4  -0.8889     0.8265  -1.075   0.2907    
## grpUmur20-40    -0.1667     0.7158  -0.233   0.8175    
## grpUmur>40       0.1667     0.7158   0.233   0.8175    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 1.753 on 30 degrees of freedom
## Multiple R-squared:  0.205,  Adjusted R-squared:  0.07248 
## F-statistic: 1.547 on 5 and 30 DF,  p-value: 0.2053
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   20-40
## 5              ALIP ASMADI     6      1    2     Mod-1   20-40
## 6 IRAWAN EKOBOEDJO MARGONO     2      1    2     Mod-1   20-40

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