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This book can be used as a stand-alone resource for working...

One can think of countries that traversed the twentieth century free from war, revolution, or social upheaval. Such countries, however, are far outnumbered by those that struggled, often constantly, with severe internal conflicts, fought in bloody wars, or were attacked by their neighbors and deprived of their sovereignty. Poland is one of the more startling examples of a country subjected to a steady stream of trials and tribulations from Hitler's Nazi Germany through decades of Soviet repression. The Spring Will Be Ours, by one of Poland's leading historians, is the first book...

This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the basics of Bayesian data analysis and its Python implementation are presented. Since surveys are widely used as the primary method to collect data, and ultimately information, on attitudes, interests, and opinions of customers and constituents, these tools are vital for private or public sector policy decisions.

As a compact volume, this book uses case...

This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of:

1. statistical, econometric, and machine learning techniques;

2. data handling capabilities;

3. at least one programming language.

Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer...

This book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems to direct data-driven decisions. Readers will explore methods for extracting information from data, work with simple and complex systems, and meld multiple forms of analytics for a more nuanced understanding of data science. The methods can be readily applied to business problems such as demand measurement and forecasting, predictive modeling, pricing analytics including elasticity estimation, customer satisfaction assessment, market research,...