Regresi Linear

investment <- c(50, 55, 60, 65, 70, 75, 80, 85, 90, 95)
output <- c(200, 220, 230, 240, 260, 270, 280, 300, 310, 320)

data <- data.frame(investment, output)

print(data)

##    investment output
## 1          50    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 <- lm(output ~ investment, data=data)

summary(model)

## 
## Call:
## lm(formula = output ~ investment, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -3.2727 -2.8636  0.2727  2.7273  3.8182 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 70.54545    5.02802   14.03 6.46e-07 ***
## investment   2.65455    0.06803   39.02 2.05e-10 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.09 on 8 degrees of freedom
## Multiple R-squared:  0.9948, Adjusted R-squared:  0.9941 
## F-statistic:  1523 on 1 and 8 DF,  p-value: 2.045e-10

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