analisis regresi sederhana

• deskripsi data data cuaca harian diperoleh dari kaggle yang memuat temperature minimum dan maksimum
• import data

library(readxl)
data <- read_excel("C:/data/data weather dila.xlsx")
data

## # A tibble: 149 x 2
##    MaxTemp MinTemp
##      <dbl>   <dbl>
##  1    25.6    22.2
##  2    28.9    21.7
##  3    26.1    22.2
##  4    26.7    22.2
##  5    26.7    21.7
##  6    26.7    21.7
##  7    28.3    22.8
##  8    26.7    22.2
##  9    27.2    22.8
## 10    25.6    21.7
## # i 139 more rows

• statistika deskriptif

summary(data)

##     MaxTemp         MinTemp     
##  Min.   :23.89   Min.   :17.78  
##  1st Qu.:26.67   1st Qu.:21.11  
##  Median :27.78   Median :21.67  
##  Mean   :28.57   Mean   :21.63  
##  3rd Qu.:31.11   3rd Qu.:22.22  
##  Max.   :34.44   Max.   :23.33

• plot

plot(data$MinTemp,
     data$MaxTemp,
     xlab = "temperatur minimum",
     ylab = "temperatur maksimum",
     main = "Scatter Plot Temperatur")

• model regresi

model <- lm(MinTemp ~ MaxTemp, data=data)
summary(model)

## 
## Call:
## lm(formula = MinTemp ~ MaxTemp, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -3.15915 -0.50822  0.04734  0.65106  2.26956 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 15.10188    0.83945  17.990  < 2e-16 ***
## MaxTemp      0.22833    0.02926   7.803 1.03e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9265 on 147 degrees of freedom
## Multiple R-squared:  0.2929, Adjusted R-squared:  0.2881 
## F-statistic: 60.89 on 1 and 147 DF,  p-value: 1.032e-12

• Uji normalitas

shapiro.test(residuals(model))

## 
##  Shapiro-Wilk normality test
## 
## data:  residuals(model)
## W = 0.97259, p-value = 0.004461

• uji heteroskesdastisitas

library(lmtest)

## Warning: package 'lmtest' was built under R version 4.5.2

## Loading required package: zoo

## Warning: package 'zoo' was built under R version 4.5.2

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

bptest(model)

## 
##  studentized Breusch-Pagan test
## 
## data:  model
## BP = 3.3436, df = 1, p-value = 0.06746

• uji autokorelasi

dwtest(model)

## 
##  Durbin-Watson test
## 
## data:  model
## DW = 1.0026, p-value = 2.833e-10
## alternative hypothesis: true autocorrelation is greater than 0