Multivariate Data Analysis Chapter 2

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Multivariate Data AnalysisChapter 2 Examining
Your Data

• MIS 6093 Statistical Method
• Instructor Dr. Ahmad Syamil

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Chapter 2

• Introduction
• Graphical Examination of the Data
• The Nature of the Variable Examining the Shape
  of the Distribution
• Examining the Relationship Between Variables
• Examining Group Differences
• Multivariate Profiles
• Summary

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Chapter 2Missing Data

• A Simple Example of a Missing Data Analysis
• Understanding the Reasons Leading to Missing Data
• Ignorable Missing Data
• Other Types of Missing Data Processes
• Examining the Patterns of Missing Data
• Diagnosing the Randomness of the Missing Data
  Process

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Chapter 2Missing Data Cont.

• Approaches for Dealing with Missing Data
• Use of Only Observations with Complete Data
• Delete Case(s) and/or Variable(s)

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Chapter 2Missing Data Cont.

• Imputation Methods
• Using All-Available Information as the Imputation
  Technique
• The Replacement of Missing Data
• Case substitution
• Mean substitution
• Cold deck imputation
• Regression imputation
• Multiple imputation
• Model-based Procedures

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Chapter 2 Missing Data Cont.

• An Illustration of Missing Data Diagnosis
• Examining the Patterns of Missing Data
• Diagnosing Randomness of the Missing Data
• Remedies for Missing Data
• A Recap of the Missing Value Analysis
• Summary

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Chapter 2Outliers

• Detecting Outliers
• Univariate Detection
• Bivariate Detection
• Outlier Designation
• Outlier Description and Profiling
• Retention or Deletion of the Outlier

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Chapter 2Outliers Cont.

• An Illustrative Example of Analyzing Outliers
• Univariate and Bivariate Detection
• Multivariate Detection
• Retention or Deletion of the Outliers

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Chapter 2Testing the Assumptions of Multivariate
Analysis

• Assessing Individual Variables Versus the Variate
• Normality
• Graphical Analysis of Normality
• Statistical Tests of Normality
• Remedies for Nonnormality

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Chapter 2Testing the Assumptions of Multivariate
Analysis Cont.

• Homoscedasticity
• Graphical Tests of Equal Variance Dispersion
• Statistical Tests for Homoscedasticity
• Remedies for Heteroscedasticity

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Chapter 2Testing the Assumptions of Multivariate
Analysis Cont.

• Absence of Correlated Errors
• Identifying Correlated Errors
• Remedies for Correlated Errors
• Data Transformations
• Transformations to Achieve Normality and
  Homoscedasticity
• Transformations to Achieve Linearity
• General Guidelines for Transformations

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Chapter 2Testing the Assumptions of Multivariate
Analysis Cont.

• An Illustration of Testing the Assumptions
  Underlying Multivariate Analysis
• Normality
• Homoscedasticity
• Linearity
• Summary

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Chapter 2

• Summary
• Questions