Data Input

investment <- c(20, 55, 60, 65, 70, 75, 80, 85, 90, 95)
output <- c(200, 220, 230, 240, 260, 270, 280, 300, 310, 320)

Membuat Data Frame

data <- data.frame(investment, output)

Melihat Seklilas Data

print(data)
##    investment output
## 1          20    200
## 2          55    220
## 3          60    230
## 4          65    240
## 5          70    260
## 6          75    270
## 7          80    280
## 8          85    300
## 9          90    310
## 10         95    320

Model Regresi Linear

model <- lm(output ~ investment, data=data)

Summary Model

summary(model)
## 
## Call:
## lm(formula = output ~ investment, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -17.709 -12.331  -1.954  10.924  23.339 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 141.7762    16.5605   8.561 2.67e-05 ***
## investment    1.7442     0.2285   7.633 6.11e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 14.85 on 8 degrees of freedom
## Multiple R-squared:  0.8793, Adjusted R-squared:  0.8642 
## F-statistic: 58.27 on 1 and 8 DF,  p-value: 6.112e-05

PLot Data dan Garis Regresi

plot(data$investment, data$output,
     xlab = "Investment (Juta Dolar)",
     ylab = "(Output (Juta Unit)",
     main = "Regresi Linear antara Investasi dan Output Industri")
abline(model, col="blue", lwd=2)