library(psych)
library(tidyverse)
library(rstatix)
library(report)
library(here)Anova
Fungsi Anova
- Menguji perbedaan variasi antar kelompok (lebih dari 2) variabel yang akan kita uji
- Kita akan menguji household income and happiness
- Research Question: apakah terdapat perbedaan tingkat kebahagiaan ditinjau dari tingkat pendapatan?
Library
Membaca data
- data pengukuran tingkat kebahagiaan
- tingkat DIY
income <- read_csv(here("datasets", "income_happiness_diy.csv"))
str(income)spc_tbl_ [913 × 4] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
$ Provinsi : chr [1:913] "Di Yogyakarta" "Di Yogyakarta" "Di Yogyakarta" "Di Yogyakarta" ...
$ Income_ind: num [1:913] 5 5 5 NA 5 4 1 3 4 5 ...
$ Income_hh : num [1:913] 5 5 5 5 3 4 2 1 1 1 ...
$ Happiness : num [1:913] 6 8 7 6 6 6 9 8 5 8 ...
- attr(*, "spec")=
.. cols(
.. Provinsi = col_character(),
.. Income_ind = col_double(),
.. Income_hh = col_double(),
.. Happiness = col_double()
.. )
- attr(*, "problems")=<externalptr>
Visualisasi awal
income |> ggplot(aes(Income_hh, Happiness, color = Income_hh)) +
geom_jitter()
Membuat boxplot
income |> mutate(income_fct = as.factor(Income_hh)) |> ggplot(aes(income_fct, Happiness, color=Income_hh)) +
geom_boxplot()
Deskriptif
income |>
group_by(Income_hh) |>
get_summary_stats(Happiness, type = "mean_sd")# A tibble: 5 × 5
Income_hh variable n mean sd
<dbl> <fct> <dbl> <dbl> <dbl>
1 1 Happiness 58 8.22 1.03
2 2 Happiness 73 8.10 1.03
3 3 Happiness 123 7.50 1.26
4 4 Happiness 288 7.58 1.46
5 5 Happiness 371 7.17 1.46
Uji anova
beda <- aov(Happiness~Income_hh, data=income)
summary(beda) Df Sum Sq Mean Sq F value Pr(>F)
Income_hh 1 87.2 87.24 45.71 2.45e-11 ***
Residuals 911 1738.8 1.91
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Effect Size
- A small effect size is about .01.
- A medium effect size is about .06.
- A large effect size is about .14.
report(beda)The ANOVA (formula: Happiness ~ Income_hh) suggests that:
- The main effect of Income_hh is statistically significant and small (F(1,
911) = 45.71, p < .001; Eta2 = 0.05, 95% CI [0.03, 1.00])
Effect sizes were labelled following Field's (2013) recommendations.