Discover millions of ebooks, audiobooks, and so much more with a free trial

Only $11.99/month after trial. Cancel anytime.

DataViz: How to Choose the Right Chart for Your Data: Bite-Size Stats, #7
DataViz: How to Choose the Right Chart for Your Data: Bite-Size Stats, #7
DataViz: How to Choose the Right Chart for Your Data: Bite-Size Stats, #7
Ebook81 pages1 hour

DataViz: How to Choose the Right Chart for Your Data: Bite-Size Stats, #7

Rating: 0 out of 5 stars

()

Read preview

About this ebook

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!

 

Discover the world of DataViz. Get this book, TODAY!

LanguageEnglish
PublisherLee Baker
Release dateJul 23, 2021
ISBN9798201312480
DataViz: How to Choose the Right Chart for Your Data: Bite-Size Stats, #7

Read more from Lee Baker

Related to DataViz

Titles in the series (7)

View More

Related ebooks

Business For You

View More

Related articles

Reviews for DataViz

Rating: 0 out of 5 stars
0 ratings

0 ratings0 reviews

What did you think?

Tap to rate

Review must be at least 10 words

    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

    Enjoying the preview?
    Page 1 of 1