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IV : Prescriptive Analytics and Optimization
1
Welcome
Authors
Live Analytics Lab
Syllabus
I : Data Fundamentals and Preparation
Foundations of Data
2
Basic Concepts of Data
3
Structured, Semi-structured and Unstructured Data
4
Data in Organizations
5
Big Data
Data for Decision Making and Preparation
6
Role of Data in Decision Making
7
Data Types by Levels of Measurement
8
Meaning and Rationale of Data Analysis
9
Data Preparation: Cleaning, Munging, Normalization and Transformation
II : Exploratory and Confirmatory Data Analysis
Types of Data Analysis
10
Descriptive Data Analysis
11
Exploratory Data Analysis
12
Confirmatory Data Analysis
Analysis Tools with R
13
Univariate Data Analysis with R
14
Bivariate Data Analysis with R
15
Multivariate Data Analysis Tools
III : Predictive Analytics and Modeling Techniques
Methods I: Regression Techniques
16
Multiple Regression
17
Logistic Regression
18
Mediation Analysis
19
Moderation Analysis
20
Implementation of Methods with R
Methods II: Multivariate Analysis
21
Factor Analysis
22
Cluster Analysis
23
Implementation of Advanced Methods with R
IV : Prescriptive Analytics and Optimization
Linear and Integer Optimization
24
Linear Programming
25
Integer Programming
Network Optimization and Simulation
26
Network Optimization
27
Simulation Modelling
References
IV : Prescriptive Analytics and Optimization
Module IV · 4 Topics
Linear and Integer Optimization
23
Linear Programming
24
Integer Programming
Network Optimization and Simulation
25
Network Optimization
26
Simulation Modelling
23
Implementation of Advanced Methods with R
24
Linear Programming