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Diterbitkan olehAgi Hermawan Telah diubah "9 tahun yang lalu
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COMPARISON ANALYSIS CORRELATION ANALYSIS AND CAUSAL ANALYSIS Dr. Muhamad Yunanto, MM.
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COMPARISON ANALYSIS
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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
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Independent Sample Test Varians kedua populasi diketahui. Varians kedua populasi tidak diketahui.
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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
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Paired Sample Test (2) T - Test : One Way ANOVA : Multiple Sample Test
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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)
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CORRELATION ANALYSIS
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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
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Bivariate Correlation
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Pearson Product Moment Correlation Interval and Normally Dist Spearman Rank Order Correlation Ordinal Scale Kappa dan Gamma Ordinal Scale Chi Square Nominal Scale
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Correlation Coefficient
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Multivariate Correlation R Square in Regression Single vs Multiple, Interval Scale and Normally Distributed Canonical Correlation Multiple vs Multiple, Interval Scale and Normally Distributed
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CAUSAL ANALYSIS
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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
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History of Causal Analysis Galton (1855) Regression Analysis Pearson (1896) Correlation Analysis Wright (1924) Path Analysis Joreskog (1970) SEM
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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
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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
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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)
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SELAMAT BELAJAR
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