Transcript 04 Analisis Perbandingan dan Hubungan.

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 2nd 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 2nd Ed, Sharpe, 2012
Ch. 13 & Ch. 14 : Business Statistics, Groebner, 2011
Ch. 10 : Marketing Research, Wrenn, 2002
Bivariate Correlation
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 2nd, Leech, 2005
Ch. 11 : Marketing Research, Malhotra, 2007
History of Causal Analysis
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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