Korelasi Pearson

Pengujian A/B di R

Lauryn Burleigh

Data Scientist

Asumsi korelasi Pearson

  • Memilih uji korelasi: sifat data
  • Korelasi Pearson
    • Linear
    • Distribusi normal

Garis linear di grafik meningkat dari kiri bawah ke kanan atas.

Grafik distribusi normal standar.

Pengujian A/B di R

Korelasi Pearson dan uji A/B

  • Grup A: Pizza Keju
  • Grup B: Pizza Pepperoni

 

  • Hubungan waktu makan pizza dan tingkat kenikmatan

Mengabaikan grup

  • H0: tidak ada hubungan antara waktu makan dan kenikmatan pizza

Tiap grup

  • H0: tidak ada hubungan antara waktu makan dan kenikmatan Pizza Keju
  • H0: tidak ada hubungan antara waktu makan dan kenikmatan Pizza Pepperoni
Pengujian A/B di R

Tentukan ukuran sampel

  • r efek yang diharapkan (dari cor())
  • sig.level untuk menolak H0
library(pwr)
pwr.r.test(r = 0.3, power = 0.80, 
           sig.level = 0.05)

    approximate correlation power 
 calculation (arctangh transformation) 

              n = 84.07364
              r = 0.3
      sig.level = 0.05
          power = 0.8
    alternative = two.sided
Pengujian A/B di R

Menilai linearitas

ggplot(pizza, aes(x = enjoyment, 
                  y = time)) + 
    geom_point()

Scatter plot hubungan linear positif antara kenikmatan (sumbu x) dan waktu (sumbu y).

ggplot(pizza, aes(x = enjoyment, 
                  y = time)) + 
    geom_point()

Scatter plot hubungan linear positif antara kenikmatan (sumbu x) dan waktu (sumbu y), dengan satu klaster titik di kiri bawah dan klaster lain yang jelas di kanan atas.

Pengujian A/B di R

Menilai kenormalan

shapiro.test(pizza$time)

    Shapiro-Wilk normality test
data:  pizza$time
W = 0.98686, p-value = 0.4282
  • Data berdistribusi normal
shapiro.test(pizza$enjoyment)

    Shapiro-Wilk normality test
data:  pizza$enjoyment
W = 0.98916, p-value = 0.5971
  • Data berdistribusi normal
Pengujian A/B di R

Pearson mengabaikan grup

cor.test(~ time + enjoyment, 
         data = pizza, 
         method = "pearson")

 

Proporsi varians: cor^2

0.30^2

[1] 0.09

Pearson's product-moment correlation

data:  time and enjoyment
t = 22.304, df = 88, p-value = 0.0218
alternative hypothesis: true correlation
is not equal to 0
95 percent confidence interval:
 0.8833166 0.9479256
sample estimates:
      cor 
0.3021878
Pengujian A/B di R

Pearson dalam tiap grup

cor.test(~ time + enjoyment, 
         data = pizza, 
         subset = 
             (Topping == "Cheese"),
         method = "pearson")

Pearson's product-moment correlation

data:  Time and Enjoy
t = 11.121, df = 98, p-value < 2.2e-16
alternative hypothesis: true correlation 
is not equal to 0
95 percent confidence interval:
 0.6451710 0.8226595
sample estimates:
     cor 
0.746935
Pengujian A/B di R

Analisis daya (power)

Pearson mengabaikan grup:

Pearson's product-moment correlation

data:  time and enjoyment
t = 22.304, df = 88, p-value = 0.0218
alternative hypothesis: true 
correlation is not equal to 0
95 percent confidence interval:
 0.8833166 0.9479256
sample estimates:
      cor 
0.3021878

library(pwr)
pwr.r.test(r = 0.302, n = 100, 
           sig.level = 0.022)

     approximate correlation power 
  calculation (arctangh transformation) 

              n = 100
              r = 0.302
      sig.level = 0.022
          power = 0.7853514
    alternative = two.sided
Pengujian A/B di R

Ayo berlatih!

Pengujian A/B di R

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