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Weather and climate resources for World Meteorological Day 23 March. Maths ideas. Tim Harford’s guide to statistics in a misleading age. BBC More or Less (@BBCMoreOrLess) More or Less. Information is Beautiful David McCandless is one of the best-known data story-tellers. WTF Visualizations lots of examples of charts that make no sense and also horrendous design choices. Extension What kinds of critical questions can we ask of texts. Analyzing and Creating Infographics – EDDA.

Analyzing and Creating Infographics Grade Level Subject Area This lesson can be used for math, science, history or English.

Analyzing and Creating Infographics – EDDA

Since it is introducing a skill once students have the skill it can be used to introduce content in the core content areas. Author Nicole Edwards, Skyline High School Introduction ave you been looking for new ways to bring in visual learning to your students that connects to a generation who lives on Facebook, twitter, and Instagram? Overview If you are not familiar with what an infographic is, it is a text that presents information/data along with visual representation (click here to see an infographic on infographics). This lesson begins by introducing the vocabulary words students will need to know to understand the infographic along with introducing students to what an infographic is.

Learning Outcomes Lesson 1: Introducing an Infographic Lesson 2: Analyzing an Infographic Lesson 3: Creating an Infographic Duration Lesson 1 55 Minutes Lesson 2 55 Minutes Context 1. 2. 3. Creating Data Literate Students. “[A] great resource!”

Creating Data Literate Students

– 2017 conference attendee How to access: Your high school students are swimming in data. From BuzzFeed quizzes to charts and tables in textbooks, from statistics flouted by politicians to figuring out what student loans really mean, data plays a big role in how they navigate the world. Data — both raw and displayed in visualizations — can clarify or confuse, confirm or deny, persuade or deter. There is growing recognition among librarians that students are either making poor decisions about the quality of statistics, data, and related visualizations or that they lack the ability to comprehend these resources altogether.

Librarians and classroom educators need to be as fluent with quantitative data as they are with text in order to support high schoolers as they engage with data in formal and informal settings. Statistics and data comprehension data as argument data visualization Table of Contents Cover IntroductionKristin Fontichiaro, Jo Angela Oehrli, Amy Lennex. Calling Bullshit — Videos. In Spring 2017, we taught the course for the first time as a series of ten hour-long lectures. These lectures were recorded using multiple cameras and edited to form a video series. We have divided up every lecture into a set of a shorter segments; each segment should more or less stand alone on its own merits. The full playlist of all course videos is available on the UW Information School's YouTube channel.

Lecture 1: An Introduction to Bullshit March 29, 2017 1.1 Introduction to Bullshit.Bullshit is everywhere, and we've had enough. 1.2 Calling Bullshit on Ourselves.Jevin uses data graphics to boast about explosive growth at our website — and Carl calls bullshit. 1.3 Brandolini's Bullshit Asymmetry Principle. 1.4 Classroom Discussion. 1.5 The Philosophy of Bullshit.How do we define bullshit? Lecture 2: Spotting Bullshit. Lies, Damned Lies, and Statistics. How to spot a misleading graph. How Writers Use Misleading Graphs To Manipulate You. In this post-truth era, graphs are being used to skew data and spin narrative like never before. Especially with the velocity at which some of these topics spread across social media.

All it takes is a single graph from a less-than-reputable source, blasted out to a list of followers, to spread a false narrative around the world. We have already seen this happen many times during the COVID-19 response, which is why we added a new section featuring a few of those misleading graphs! Now the data doesn’t even have to be bad–it could just be presented in a misleading way. I mean, there is a whole Wikipedia page, Reddit community, and hundreds of articles about how graphs can be used to misinform readers. Now, I can’t make these data-skewing creators stop, but I can help you spot these misleading graphs when they crop up. Not a designer? Also, following data visualization best practices ensures that your graphs are always clear and understandable.