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Multivariate Data Analysis Chapter 2

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Imputation Methods. Using All-Available Information as the Imputation Technique ... deck imputation. Regression imputation. Multiple imputation. Model-based ... – PowerPoint PPT presentation

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Title: Multivariate Data Analysis Chapter 2


1
Multivariate Data AnalysisChapter 2 Examining
Your Data
  • MIS 6093 Statistical Method
  • Instructor Dr. Ahmad Syamil

2
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

3
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

4
Chapter 2Missing Data Cont.
  • Approaches for Dealing with Missing Data
  • Use of Only Observations with Complete Data
  • Delete Case(s) and/or Variable(s)

5
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

6
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

7
Chapter 2Outliers
  • Detecting Outliers
  • Univariate Detection
  • Bivariate Detection
  • Outlier Designation
  • Outlier Description and Profiling
  • Retention or Deletion of the Outlier

8
Chapter 2Outliers Cont.
  • An Illustrative Example of Analyzing Outliers
  • Univariate and Bivariate Detection
  • Multivariate Detection
  • Retention or Deletion of the Outliers

9
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

10
Chapter 2Testing the Assumptions of Multivariate
Analysis Cont.
  • Homoscedasticity
  • Graphical Tests of Equal Variance Dispersion
  • Statistical Tests for Homoscedasticity
  • Remedies for Heteroscedasticity

11
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

12
Chapter 2Testing the Assumptions of Multivariate
Analysis Cont.
  • An Illustration of Testing the Assumptions
    Underlying Multivariate Analysis
  • Normality
  • Homoscedasticity
  • Linearity
  • Summary

13
Chapter 2
  • Summary
  • Questions
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