Syllabus

The complete module-and-topic map of the book, taking you across the full analytics spectrum — from preparing data to prescribing decisions. Click any module to open its overview, or jump straight to a numbered topic.

Four-Module Analytics Spectrum · 26 Topics

IData Fundamentals and Preparation8 topics

Foundations of Data

1Basic Concepts of Data 2Structured, Semi-structured and Unstructured Data 3Data in Organizations 4Big Data

Data for Decision Making and Preparation

5Role of Data in Decision Making 6Data Types by Levels of Measurement 7Meaning and Rationale of Data Analysis 8Data Preparation: Cleaning, Munging, Normalization and Transformation

IIExploratory and Confirmatory Data Analysis6 topics

Types of Data Analysis

9Descriptive Data Analysis 10Exploratory Data Analysis 11Confirmatory Data Analysis

Analysis Tools with R

12Univariate Data Analysis with R 13Bivariate Data Analysis with R 14Multivariate Data Analysis Tools

IIIPredictive Analytics and Modeling Techniques8 topics

Methods I: Regression Techniques

15Multiple Regression 16Logistic Regression 17Mediation Analysis 18Moderation Analysis 19Implementation of Methods with R

Methods II: Multivariate Analysis

20Factor Analysis 21Cluster Analysis 22Implementation of Advanced Methods with R

IVPrescriptive Analytics and Optimization4 topics

Linear and Integer Optimization

23Linear Programming 24Integer Programming

Network Optimization and Simulation

25Network Optimization 26Simulation Modelling