library(readxl)
## Warning: package 'readxl' was built under R version 4.3.2
data <- read_xlsx("D:/Statistika dan Sains Data/Semester 4/Analisis Regresi/Anreg 4.3.xlsx")
## New names:
## • `` -> `...1`
data
## # A tibble: 24 × 3
##     ...1 Units Minutes
##    <dbl> <dbl>   <dbl>
##  1     1     1      23
##  2     2     2      29
##  3     3     3      49
##  4     4     4      64
##  5     5     4      74
##  6     6     5      87
##  7     7     6      96
##  8     8     6      97
##  9     9     7     109
## 10    10     8     119
## # ℹ 14 more rows

membuat model linear regresi

model <- lm(Minutes~Units, data<- data)
summary(model)
## 
## Call:
## lm(formula = Minutes ~ Units, data = data <- data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -31.603 -14.801  -0.045  17.335  29.092 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  37.2127     7.9853    4.66  0.00012 ***
## Units         9.9695     0.7218   13.81 2.56e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 18.75 on 22 degrees of freedom
## Multiple R-squared:  0.8966, Adjusted R-squared:  0.8919 
## F-statistic: 190.7 on 1 and 22 DF,  p-value: 2.556e-12

Persamaan Regresi 4.3

Y=37.2127+9.9695X

Interprestasi

Ketika x mengalami kenaikan satu satuan maka y mengalami kenaikan sebesar 9.9695 Ketika x sama dengan 0 maka dugaan rataan y adalah 37.2127