Practical Methods For Design And Analysis of Complex Surveys

The three parts of this book on survey methodology combine an introduction to basic sampling theory, engaging presentation of topics that reflect current research trends, and informed discussion of the problems commonly encountered in survey practice.

This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic methods.

Market Research Fundamentals Training Program (Course 2 of 3)

Gain practical experience in R for Data Analysis, Machine Learning and Artificial Intelligence. Become a Data Scientist.

Certified Manager of Quality and Organizational Excellence (CMQ/OE) Exam Preparation Course.

Mastering the different root cause analysis methodologies and how they can be conducted.