DataViz: How to Choose the Right Chart for Your Data: Bite-Size Stats, #7
By Lee Baker
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About this ebook
**DataViz: How to Choose the Right Chart for Your Data**
Unlock the true potential of your data with "DataViz: How to Choose the Right Chart for Your Data." This friendly, chatty, and slightly technical guide will transform the way you present information, making your data visualizations clear, engaging, and impactful.
**Why this book is perfect for you:**
- **Engage your audience:** Learn how to create charts that captivate and communicate effectively.
- **Maximize clarity:** Understand which data belongs on which axis for maximum clarity.
- **Choose the right chart:** Discover the ideal chart types for various data sets, ensuring you always pick the best one.
- **Perfect your style:** Get tips on styling your charts to make them visually appealing and easy to understand.
- **Critical review skills:** Learn how to review your charts critically, removing unnecessary elements and enhancing readability.
- **Big Picture Flowchart:** Use our Ultra-High-Definition flowchart to guarantee you select the right chart every time.
- **Boost your confidence:** By the end of this guide, you'll know more about plotting charts than most of your peers.
Creating effective data visualizations is crucial in fields like Data Science, business intelligence, and statistics. A well-crafted chart can convey complex information clearly and inspire action. Unfortunately, many struggle with this skill, resulting in charts that fail to engage.
In "DataViz: How to Choose the Right Chart for Your Data," award-winning author and data visualization expert Lee Baker takes you through the essentials of chart creation. You'll start with the basics, learning about different graph types and which data belongs on which axis. Then, you'll explore various chart options, understanding when and how to use each one.
You'll also dive into the art of chart styling, learning how to review your charts with a critical eye and make necessary adjustments. Our exclusive DataViz – The Big Picture flowchart provides a comprehensive guide to selecting the perfect chart every time, ensuring your data is presented in the most effective way possible.
Whether you're preparing a study, presentation, thesis, or any other data-driven project, this book will equip you with the skills to create inspirational and effective graphics, regardless of your audience.
Ready to become a data visualization pro? Grab your copy of "DataViz: How to Choose the Right Chart for Your Data" today and start transforming your data into compelling stories!
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Book preview
DataViz - Lee Baker
Preface
Data visualisation is sexy – probably the sexiest part of statistics, Data Science, business intelligence and many other fields too.
And it can make or break your study!
Few people that have to create charts as part of their study know and understand how to create charts for maximum effectiveness, and as a result struggle to engage their audience.
And that’s a shame, because a well-crafted chart has the potential to change the world!
Charts really are that important!
DataViz: How to Choose the Right Chart for Your Data is a short guide to all the different types of charts you’ll commonly encounter in statistics.
It is a snappy little non-threatening book about everything you ever wanted to know (but were afraid to ask) about the craft of creating inspirational graphics for your study, presentation, thesis, or just about any occasion – irrespective of your audience.
First, I’ll explain about the different types of graphs you’ll use.
Then I’ll show you which data goes on which axis.
I’ll show you the different types of charts to use, and how to choose which ones to use.
We’ll move on to how to style your charts and review them with a critical eye to decide what should go on your graph, and – more importantly – what you should take off.
Finally, I’ll introduce you to DataViz – The Big Picture, an Ultra-High-Definition flowchart that will guarantee that you get the right chart first time, every time!
By the time you’ve read this short book, you’ll more about plotting charts than pretty much everyone around you!
This book is not written for statisticians. Nor is it written by a statistician. I may have worked as a statistician for several years, but I was actually trained as a Physicist, and these days I have my own Data Science company.
My lack of formal training in statistics is not a weakness, though. On the contrary, it is a strength. I have my own struggles with statistics, so I understand where the hard bits are, and I know how to explain them to others in plain English without using difficult to understand technical terminology.
While this version of the book is complete, it remains a work-in-progress in the sense that in this digital, online, always-connected world we’re living in, nothing is ever truly finished.
So, as this book is for you, I want you to reach out to me and tell me what you think of DataViz: How to Choose the Right Chart for Your Data:
Tell me how I can improve it
Tell me which bits I didn’t explain very well
Tell me what I’ve missed out that would have helped you
The next version will be so much better for it.
I hope you enjoy this book, are inspired by it and will check out my other books.
At the end of this book is a link where you can leave your feedback, and I look forward to hearing from you!
Lee Baker
Introduction
Graphs don’t lie.
You put some numbers into a spreadsheet, tell it which graph you want, and out pops a faithful representation of your data. If you give it the numbers 70, 63 and 60, it will plot them on your chosen graph, even as a pie chart. It won’t change the numbers, give them political spin or otherwise misrepresent them. It doesn’t know how to.
People, on the other hand, do.
Graphs might not lie, but if you plot truthful data on an inappropriate graph, you’ll be guilty of misleading your audience, whether wittingly or otherwise.
If you had to kill a cat every time you used a chart inappropriately, you’d take a lot more care with your choice of graphic and on how you presented it, wouldn’t you? This is the kind of