Book Summary of "Evidence: How to Speak with Data" In the book "Evidence: How to Speak with Data", Howard S. Becker elaborates on how to use data and statistical analysis to support decision-making and argumentation. The book is divided into four main parts, each of which explores different aspects of data analysis and evidence presentation in detail. Part I: Basic Knowledge1. Introduction to Statistics - Definition of Statistics: Statistics is the science of collecting, analyzing, interpreting, displaying and simulating data. - Purpose of Data Analysis: Use data to draw conclusions, make predictions or make decisions. - Classification of Statistical Methods: Descriptive Statistics and Inferential Statistics. 2. Data and Sampling - Data Type: Qualitative Data and Quantitative Data. - Sample Concept: Select a representative sample from the population for research. - Sampling Method: Random sampling techniques, such as simple random sampling, stratified sampling, etc. Part II: Data Analysis3. Exploratory Data Analysis - Purpose of EDA: Understand the basic characteristics of the data and possible patterns. - Visual Exploration Methods: Histograms, box plots, etc. are used for data visualization. - Numerical Exploration Methods: Central tendency measures (mean, median, mode) and variability measures (standard deviation, quartiles). 4. Hypothesis Testing - Basic Concepts: Propose a hypothesis (null hypothesis) and use samples to test whether this hypothesis is true. - Type I and II Errors: The risk of incorrectly rejecting or accepting the null hypothesis. - Common Test Methods: T-test, chi-square test, etc. Part III: Data Processing5. Data Cleaning and Preparation - Data Cleaning Steps: Identify and handle missing values, outliers, duplicate data, etc. - Data Transformation: Perform necessary formatting and standardization on the data. - Feature Engineering: Create new variables or change the form of existing variables to improve the model effect. 6. Data Analysis Tools - Introduction to Statistical Software: Excel, SPSS, R, Python, etc. - Database Management: Basic concepts of SQL and NoSQL databases. - Programming Basics: Basic data operations and automated scripting. Part IV: Application of Evidence7. Data Communication - Principles of Effective Communication: Clarity, Accuracy, and Relevance. - Selection and Production of Charts: How to Choose the Right Type of Charts to Present Data. - Storytelling Skills: Use narrative structures to enhance the appeal of data. 8. Ethics and Responsibilities - Data Privacy: The Importance of Protecting Personal Privacy and Data Security. - Bias and Fairness: Ensure that data analysis is not influenced by preconceived notions. - Transparency: Disclose data sources, explain analysis methods, and possible limitations. The above is an outline of the book "Evidence: How to Speak with Data". Each chapter is divided into key sections, and the core ideas of each section are summarized, aiming to provide readers with a clear framework to understand and master the concepts and methods discussed in the book.

Regarding the book "Evidence: How to Speak with Data" by Howard S. Becker, the following are selected wonderful sentences or paragraphs, which are profound, unique in perspective, beautiful in language, full of wisdom, or creative. For readers, these excerpts will try to maintain the professionalism and essence of the original book. --- 1. "Data are not just numbers, they are fragments of the world, simplified representations of complex reality, and tools for us to understand and explain the world." 2. "In the ocean of data, we need to learn to swim, not only to avoid drowning, but also to be able to fish out valuable information from it." 3. "Statistics is not magic, it cannot create something out of nothing, but it can help us find order in chaos and certainty in uncertainty." 4. "Data visualization is an art that requires us to transform boring numbers into fascinating images to reveal the stories hidden in the data." 5. "There is no perfect data, only good enough data. The pursuit of perfection often hinders our progress, while good enough data is enough to support us to make wise decisions." 6. "In the era of big data, what matters is not how much data you have, but how much wisdom you can extract from the data." 7. "Data science is not just a technology, but also a way of thinking. It requires us to have both rigorous logical reasoning ability and rich imagination and creativity." 8. "Data is like a mirror. It can reflect our biases and blind spots. Therefore, when using data, we must always be vigilant and self-reflective." 9. "Data will not lie, but liars will use data. In the world of data, we need to learn to distinguish between truth and falsehood and expose lies." 10. "Data is dead, people are alive. We cannot be led by data, but should use data to serve our goals and visions." 11. "When collecting and analyzing data, we must always remember that the quality of data is more important than quantity, and accuracy is more valuable than generalities." 12. "Data science is a practical philosophy that requires us to find a balance between theory and practice and to build a bridge between ideals and reality." 13. "Data can reveal the regularities and patterns of the world, but it cannot explain why these regularities and patterns exist. This requires us to use the wisdom of philosophy and science to explore and understand." 14. "In the world of data, there is no absolute truth, only a process of constantly approaching the truth." 15. "Data is a language with its own grammar and vocabulary. To become masters of data, we must first learn this language." 16. "Data is objective, but our interpretation of data is subjective. Therefore, when presenting data, we must try to be objective and fair." 17. "Data can be used not only to describe reality, but also to predict the future. But please note that prediction is not destiny, it is just a possibility." 18. "When sailing in the ocean of data, we need to have clear goals and a firm sense of direction, otherwise we can easily lose our way." 19. "Data science is an art of collaboration. It requires us to work with people from different backgrounds and professions to solve problems together." 20. "Finally, remember: although data is powerful, it is not omnipotent. When using data, please remain humble and in awe." --- These sentences and paragraphs are intended to capture the core ideas and wonderful arguments of Howard S. Becker in the book "Evidence: How to Speak with Data", hoping to provide readers with valuable reference and inspiration.

Title: Howard S.

Becker: A Master of Speaking with Data Howard S.< Becker is an American sociologist and writer, known for his contributions to social science methodology.

His book Evidentiary delves into how to use data for effective communication and decision-making.< The following is a detailed introduction to Becker.

Basic Personal Information Howard S.< Becker was born in 1938 and grew up in Chicago, USA.

He is an active sociological researcher and educator with a deep understanding and unique insights into the field of social sciences.< Education and Career Background Becker received a bachelor's degree in sociology from the University of Chicago and a master's and doctoral degree from Stanford University.

His academic career began at the University of California, Berkeley, and he later taught at the University of Washington and Northwestern University.< Becker's research areas include social science methodology, criminology, and educational sociology.

Writing Career Becker's writing career began in the 1960s, and his first book, Outsiders, explored the impact of social labels on individuals.< Since then, he has published a number of books, including Arts and Crafts and Telling About Society.

His books have been widely praised for explaining complex social science concepts in an easy-to-understand way.< Style and Theme Becker's writing style is characterized by clarity, rigorous logic and positivism.

He focuses on how to apply social science theories to practical problems, especially in data analysis and evidence evaluation.< The book "Evidence" is his in-depth exploration of this topic.

Personal Life Becker's personal life is relatively low-key, and he devotes most of his time to academic research and writing.< He lives in Chicago, USA with his wife and children.

Social Impact Becker's works have had a profound impact on the field of social sciences.< His research methods and theories have been widely used in fields such as sociology, criminology and education.

His works have also been translated into many languages and are popular among readers around the world.< Citations and Reviews The book "Evidence" has been well received by many authoritative media and experts.

The New York Times commented that the book is "a must-read book on how to use data for effective communication.< " Sociologist James Mahoney believes that Becker's work "provides us with a new perspective for understanding and evaluating social science evidence.

" Latest Updates Howard S.< Becker is still active in academia and continues to conduct research and write.

His latest book, The Logic of the Social Sciences, was published in 2021, further exploring methodological issues in social science research.< Overall, Howard S.

Becker is an outstanding sociologist and writer, and his work provides valuable guidance for our understanding and application of social science.