Statistical Analysis And Visualization


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Data Analytics and Visualization in Quality Analysis using Tableau


Data Analytics and Visualization in Quality Analysis using Tableau

Author: Jaejin Hwang

language: en

Publisher: CRC Press

Release Date: 2021-07-27


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Data Analytics and Visualization in Quality Analysis using Tableau goes beyond the existing quality statistical analysis. It helps quality practitioners perform effective quality control and analysis using Tableau, a user-friendly data analytics and visualization software. It begins with a basic introduction to quality analysis with Tableau including differentiating factors from other platforms. It is followed by a description of features and functions of quality analysis tools followed by step-by-step instructions on how to use Tableau. Further, quality analysis through Tableau based on open source data is explained based on five case studies. Lastly, it systematically describes the implementation of quality analysis through Tableau in an actual workplace via a dashboard example. Features: Describes a step-by-step method of Tableau to effectively apply data visualization techniques in quality analysis Focuses on a visualization approach for practical quality analysis Provides comprehensive coverage of quality analysis topics using state-of-the-art concepts and applications Illustrates pragmatic implementation methodology and instructions applicable to real-world and business cases Include examples of ready-to-use templates of customizable Tableau dashboards This book is aimed at professionals, graduate students and senior undergraduate students in industrial systems and quality engineering, process engineering, systems engineering, quality control, quality assurance and quality analysis.

Introducing Data Science for Beginners 2025 | Learn Data Analysis, Visualization & Machine Learning Basics


Introducing Data Science for Beginners 2025 | Learn Data Analysis, Visualization & Machine Learning Basics

Author: A. Ali

language: en

Publisher: Code Academy

Release Date: 2025-05-07


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Introducing Data Science for Beginners 2025 is your essential guide to understanding the fundamentals of data science, even if you have no prior experience. This beginner-friendly book breaks down core concepts such as data analysis, visualization, statistics, and the basics of machine learning. With real-world examples and simplified explanations, it helps you build a strong foundation in Python, data handling, and decision-making through data. Whether you're a student, professional, or enthusiast, this book provides the perfect starting point to enter the world of data science with confidence.

Discrete Data Analysis with R


Discrete Data Analysis with R

Author: Michael Friendly

language: en

Publisher: CRC Press

Release Date: 2015-12-16


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An Applied Treatment of Modern Graphical Methods for Analyzing Categorical DataDiscrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data presents an applied treatment of modern methods for the analysis of categorical data, both discrete response data and frequency data. It explains how to use graphical meth