Making Numbers Count: The Art and Science of Communicating Numbers

Making Numbers Count: The Art and Science of Communicating Numbers

3.0 (1 التقييمات)
2022 · الإنجليزية · كيندل
أضف إلى الرف

قيم هذا الكتاب


تصدير مجلة الكتاب

الوصف

In a world increasingly driven by data, effective communication of numbers is essential. This book serves as a groundbreaking resource, bridging the gap between complex numerical concepts and everyday comprehension. With a focus on actionable insights, the authors offer strategies to make numerical information more accessible and relatable to a wide audience.

Through a blend of engaging storytelling and practical applications, readers gain the tools needed to present data in a way that captivates and informs. The emphasis on clarity and user-friendly techniques ensures that both novices and seasoned professionals can enhance their ability to convey numerical information effectively.

تفاصيل الكتاب

تنسيق كيندل
صفحات 224 صفحات
لغة الإنجليزية
منشور يناير 11, 2022
الناشر Avid Reader Press / Simon & Schuster
رقم ISBN-10 1982165456
رقم ISBN-13 9781982165451

الأنواع

المراجعات

عرض الكل

I chose to read this book because of the author. Chip Heath is among my favourite behavioural economics authors (if you haven't read any of his books, try "Made to Stick" or "Switch") because of his ability to simplify a topic and make the discussions practical. Like other books by the Heath brothers, I'd consider this one easy to read, and even easier for those who work with numerical data, whether you consume data or present data or both. There are a few simple principles in data story-telling according to this book:* Numbers should be simplified, you don't want to overwhelm the audience with too many numbers.* Your analogy and examples should be relatable.* Inserting emotions when explaining data helps you engage with your audience better.In this book, you'll see a lot of before-and-after data presentation examples to help you make sense of the principles. Unfortunately, I can only rate this book 3/5 because some of the recommended presentation techniques (the 'after') are somehow irrelevant and are not mentioned in the actual data (the 'before'). This means that some information in the 'after' is actually an assumption since it's not mentioned in the data at all. If you work as a data analyst or a researcher and you do this, avoid this at all costs unless you're asked to build a hypothesis.That said, I recommend you read it if you want to polish your data presentation skills.

February 28th 2022
أضف إلى الرف

قيم هذا الكتاب


تصدير مجلة الكتاب