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Click to edit Master subtitle style Ch 1 1. Overview of Multivariate Methods 11
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Ch 1 CONTENT Basic concepts Instruction data 22
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Ch 1 Multivariate Analysis Univariate One variable Descriptive Bivariate Two variables Relational 33
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Ch 1 Multivariate Analysis (cont) What is variate? A linear combination of variables with empirically determined weights Weights are determined by a specific multivariate technique. Example: Multiple Regression Predicting purchase intent from income , education and family size Y = a + b1X1 + b2X2 + b3X3 44
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Ch 1 Data 55 Data Metric Nominal Ordinal Interv al Rati o Non- Metric
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Ch 1 Data (cont) Validity Reliability Consistency Reliable but invalid 66
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Ch 1 Data (cont) Improve validity and reliability What to ask How to ask Multiple variables for one concept 77
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Ch 1 Error Hypothesis Test Null hypothesis 88
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Ch 1 Error 99 Reality No impact Impact Statistical Decision Accept H0 Reject H0 Type I Error Type II Error
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Ch 1 Error Hypothesis Test Null hypothesis Type I error Probability of rejecting the null hypothesis when it is true l / significance level: .05 Type II error Probability of accepting the null hypothesis when it is false l : .20 power = 1 - “: .80 10
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This note was uploaded on 06/18/2011 for the course MGT 600+ taught by Professor Shen during the Spring '11 term at Saint Joseph's University.

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01_Chapter 01(1) - Click to edit Master subtitle style 1....

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