# COMPARISON ANALYSIS CORRELATION ANALYSIS AND CAUSAL ANALYSIS Dr. Muhamad Yunanto, MM.

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COMPARISON ANALYSIS CORRELATION ANALYSIS AND CAUSAL ANALYSIS Dr. Muhamad Yunanto, MM.

COMPARISON ANALYSIS

Training Objectives Mengetahui dan dapat melakukan analisa perbandingan (Parametric / Non Parametric) Ch. 14 : Business Statistics 2 nd Ed, Sharpe, 2012 Ch. 10 : Business Statistics, Groebner, 2011

Independent Sample Test Varians kedua populasi diketahui. Varians kedua populasi tidak diketahui.

Paired Sample Test (1) Sampel berpasangan adalah suatu kondisi dimana kedua kelompok populasi yang akan diuji dapat dipetakan satu persatu. Contoh : Pre Test vs Post Test pada siswa yang sama Uji antar Saudara kembar Identik Uji kesetiaan Suami dan Istri

Paired Sample Test (2) T - Test : One Way ANOVA : Multiple Sample Test

Non Parametric Comparison Independent Samples Mann – Whitney (Two Samples, Ordinal) Kruskal-Wallis (Multiple Samples, Ordinal) Paired Samples Sign Test, Wilcoxon (Two Samples, Ordinal) Mc Nemar Test (Two Samples, Binary) Cochran Q Test (Multiple Samples, Binary)

CORRELATION ANALYSIS

Training Objectives Mengetahui dan dapat melakukan analisa hubungan (Parametric / Non Parametric) Ch. 15 : Business Statistics 2 nd Ed, Sharpe, 2012 Ch. 13 & Ch. 14 : Business Statistics, Groebner, 2011 Ch. 10 : Marketing Research, Wrenn, 2002

Bivariate Correlation

Pearson Product Moment Correlation Interval and Normally Dist Spearman Rank Order Correlation Ordinal Scale Kappa dan Gamma Ordinal Scale Chi Square Nominal Scale

Correlation Coefficient

Multivariate Correlation R Square in Regression Single vs Multiple, Interval Scale and Normally Distributed Canonical Correlation Multiple vs Multiple, Interval Scale and Normally Distributed

CAUSAL ANALYSIS

Training Objectives Mengetahui dan dapat melakukan analisa kausal. Ch. 16, Ch. 18 & Ch. 19 : Bus Stats, Sharpe, 2012 Ch. 14 & Ch.15 : Business Statistics, Groebner, 2011 Ch 6 : SPSS for Intermediate 2 nd, Leech, 2005 Ch. 11 : Marketing Research, Malhotra, 2007

History of Causal Analysis Galton (1855) Regression Analysis Pearson (1896) Correlation Analysis Wright (1924) Path Analysis Joreskog (1970) SEM

Regression and Path Analysis Type Simple and Multiple Regression Aim : Model between Independent(s) & Dependent(s) Assumption Interval Scale, Normality, Homogenity of Variance, Non Autocorrelated, Non Multicollinearity Statistics Test F Test, T Test

Causal Analysis : ANOVA ANOVA Mengukur perbedaan efek perlakuan terhadap respons yang diukur. Dapat dianggap sebagai analisis multiple comparison, jika treatment berskala nominal. Asumption Interval Scale, Normally Distributed, Homogenity in Variance

Causal Analysis : SEM SEM =1. Covariance Structure Analysis 2. Latent Variable Analysis 3. LISREL Analysis SEM=Metode yang menggabungkan Analisis Jalur (Structural Model) dan CFA (Measurement Model)

SELAMAT BELAJAR

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