Modern Survey Analysis: Using Python for Deeper Insights

Author:   Walter R. Paczkowski
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
ISBN:  

9783030762667


Pages:   347
Publication Date:   12 September 2022
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Modern Survey Analysis: Using Python for Deeper Insights


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Overview

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 studies to illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives: Demonstrate how to extract actionable, insightful, and useful information from survey data; and Introduce Python and Pandas for analyzing survey data.

Full Product Details

Author:   Walter R. Paczkowski
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2022
Weight:   0.729kg
ISBN:  

9783030762667


ISBN 10:   3030762661
Pages:   347
Publication Date:   12 September 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Walter R. Paczkowski, PhD, has worked at AT&T, AT&T Bell Labs, and AT&T Labs. He founded Data Analytics Corp., a statistical consulting company, in 2001. Dr. Paczkowski is also a part-time lecturer of economics at Rutgers University. He is the author of Business Analytics: Data Science for Business Problems (2022), Deep Data Analytics for New Product Development (2020), Pricing Analytics: Models and Advanced Quantitative Techniques for Product Pricing (2018), and Market Data Analysis Using JMP (2016).

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