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ODL - Multivariate Methods for Data Analysis
INTRODUCTION
TOPIC 1: INTRODUCTION TO MULTIVARIATE DATA ANALYSIS
TOPIC 2: STEPWISE REGRESSION
TOPIC 3: FACTOR ANALYSIS
TOPIC 4: CLUSTER ANALYSIS
TOPIC 5: MULTIPLE DISCRIMINANT ANALYSIS
TOPIC 6: BINARY LOGISTIC REGRESSION
TOPIC 7: STRUCTURAL EQUATION MODELLING
Case-study 1: Step-wise regression and factor analysis
Case-study 2: Discriminant analysis and logistic regression
Case-study 3: Structural equation modeling
Group discussion on multivariate methods using software
ASSESSMENT
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ODL - Multivariate Methods for Data Analysis
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ODL - Multivariate Methods for Data Analysis
Topic outline
General
INTRODUCTION
Lecturer Introduction
Page
Module Introduction
Page
Supplementary Materials
Folder
TOPIC 1: INTRODUCTION TO MULTIVARIATE DATA ANALYSIS
Introduction
Page
LO1: Explain what multivariate analysis is and when to use it
Page
Self Check on multivariate analysis and its application
Quiz
LO2: Categorize Multivariate techniques
Page
Self Check on multivariate techniques
Quiz
LO3: Construct Hypotheses, Error and Power of Test
Page
Self Check on hypotheses, error, and power of test
Quiz
LO4: Explain Concepts of Correlation and Covariance
Page
Self Check on correlation and covariance
Quiz
TOPIC 2: STEPWISE REGRESSION
Introduction
Page
LO1: Determine when to apply regression analysis in analyzing a problem
Page
Self-check on determine when to apply regression analysis in analyzing a problem
Quiz
LO2: Explain how least square principle works in simple linear regression
Page
Explain how least square principle works in simple linear regression
Forum
LO3: Use dummy variables for qualitative independent variables in conjunction with multiple linear regression
Page
Self-Check on the use of dummy variables for qualitative independent variables in conjunction with multiple linear regression
Quiz
LO4: Explain the importance of assumptions compliance in linear regression
Page
Self-check on explaining the importance of assumptions compliance in linear regression model
Quiz
LO5: Interpret the role of partial correlation in conjunction with stepwise regression
Page
Self-check on interpreting the role of partial correlation in conjunction with stepwise regression.
Quiz
TOPIC 3: FACTOR ANALYSIS
Introduction
Page
LO1: Identify Factor Analysis as Interdependence Technique
Page
LO2: Explain differences between principal factor analysis and principal component analysis
Page
Self check on Differences between component analysis and common factor analysis models.
Quiz
LO3: Perfom Factorability Investigation of Data factorability investigation of data to determine the number of factors to extract.
Page
Self check on how to determine number of factors to extract.
Quiz
LO4: Interpret Factor Analysis Results
Page
Self check on the rotation of factor to ease on the factor extraction.
Quiz
LO5: Explain Concept of Factor Rotation
Page
Self check on major limitations of factor analytic techniques
Quiz
Q & A Forum
TOPIC 4: CLUSTER ANALYSIS
Introduction
Page
Identify the types of research questions addressed by cluster analysis
Page
Self check on fundamental concepts of cluster analysis and its applications.
Quiz
Understand how inter-object similarity is measured
Page
Self check on measure of distance
Quiz
Understand why different distance measures are sometimes used
Page
Self check on using t-test to test the significance of variable in a regression model.
Quiz
Understand the differences between hierarchical and non-hierarchical clustering
Page
Self check on understanding of hierarchical and non-hierarchical clustering.
Quiz
Know how to interpret the results from cluster analysis
Page
Self check on the understanding of agglomeration stages and the information which can be extracted.
Quiz
Follow the guideline for cluster validation
Page
Self check on understanding of cluster validation.
Quiz
TOPIC 5: MULTIPLE DISCRIMINANT ANALYSIS
Introduction
Page
LO1: Explain Discriminant Analysis
Page
Self check on discriminant analysis, multiple discriminant analysis and its purposes
Quiz
LO2: Explain The assumptions underlying discriminant analysis in assessing its appropriateness for a particular problem
Page
Self check on assumptions underlying discriminant analysis
Quiz
LO3: Explain Terms involved in discriminant analysis
Page
Self check on terms involved in discriminant analysis
Quiz
LO4: Interpret of discriminant analysis results
Page
Self check on interpretation of discriminant analysis results
Quiz
TOPIC 6: BINARY LOGISTIC REGRESSION
Introduction
Page
LO1: Identify Types of dependent and independent variables used in the application of logistic regression
Page
Self check on types of dependent and independent variables used in the application of logistic regression
Quiz
LO2: Describe Method used to predict the probability measures used in logistic regression
Page
Self check on the method used tp predict the probability measures used in logistic regression
Quiz
LO3: Interpret Results of binary logistic regression analysis.
Page
Self check on interpretation of results of binary logistic regression analysis
Quiz
TOPIC 7: STRUCTURAL EQUATION MODELLING
Introduction
Page
LO1: Distinguish Variables and Construct
Page
LO2: Explain Structural Equation Modeling
Page
LO3: Assess Validity of a Measurement Model
Page
LO4: Distinguish between Measurement Model and Structural Model
Page
LO5: Depict A Model Using a Path Diagram
Page
LO6: Calculate Strength of Relationship in Path Diagram
Page
Case-study 1: Step-wise regression and factor analysis
Instructions before our face-to-face meeting
Page
Key tutorial questions for Case study 1
File
Case-study 2: Discriminant analysis and logistic regression
Instruction
Page
Key tutorial questions for Case study 2
File
Case-study 3: Structural equation modeling
Instruction
Page
key tutorial questions for case study 3
File
Group discussion on multivariate methods using software
Instruction
Page
ASSESSMENT
sample of past assessments
File