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Analisis Korelasi

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Analisis Korelasi

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About this activity

Uji dan interpretasi korelasi data.

Created by

Ni Wayan Muliantari
Ni Wayan Muliantari
Indonesia

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Analisis Korelasi
 

Analisis KorelasiOnline version

Uji dan interpretasi korelasi data.

by Ni Wayan Muliantari
1

Apa tujuan utama analisis korelasi dalam data?

2

Nilai koefisien korelasi Pearson berkisar antara berapa?

3

Kapan sebaiknya menggunakan korelasi Spearman?

4

Apa arti koefisien r = 0,85 dalam korelasi Pearson?

5

Kata kunci untuk menghindari kesalahan umum korelasi adalah?

6

Apa asumsi utama untuk korelasi Pearson?

7

Bagaimana outlier mempengaruhi koefisien korelasi?

8

Apa bedanya korelasi vs kausalitas?

9

Apa arti p-value kecil dalam uji korelasi?

10

Mengapa visualisasi scatter plot penting dalam analisis korelasi?

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Korelasi mengukur arah (positif/negatif) dan kekuatan hubungan, bukan sebab akibat atau transformasi data.

Koefisien Pearson berada dalam rentang -1 hingga 1; tanda menunjukkan arah hubungan.

Spearman nonparametrik, cocok untuk hubungan monotonik atau data ordinal/non-normal.

Nilai 0,85 menunjukkan hubungan kuat positif antar variabel.

Korelasi tidak membuktikan sebab akibat; korelasi bisa muncul karena faktor lain.

Pearson mengasumsikan hubungan linier dan varians konstan; outlier bisa mempengaruhi.

Outlier bisa mendistorsi estimasi r, sehingga perlu dianalisis dampaknya.

Korelasi tidak membuktikan bahwa satu variabel menyebabkan yang lain.

P-value kecil menghasilkan penolakan hipotesis nol (tidak ada korelasi) pada tingkat signifikansi.

Scatter plot membantu memvalidasi asumsi linearitas dan mendeteksi outlier sebelum menghitung koefisien.

 
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