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# 17 Key Traits of Data Literacy

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What are the knowledge, skills, attitudes & behaviors that highly data literate people possess and demonstrate? Slides for a webinar given on January 16th https://youtu.be/KA_e1uFSWUM

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### 17 Key Traits of Data Literacy

1. 1. © 2018 Data Literacy. All rights reserved. 7 Data Types: NOIR Qualitative (categorical) Quantitative (numerical) Nominal (not ordered) Ordinal (ordered) Interval (differences) Ratio (fractions) Nominal = “Names” E.g. Gender, Color Ordinal = has order, but differences between levels is unknown E.g. Satisfaction score, level of pain Interval – has order, differences between values is consistent, but 0 does not mean “none” E.g. Temperature in °F Ratio – has order, differences between values is consistent, and 0 means “none” E.g. Height of people in the room
2. 2. © 2018 Data Literacy. All rights reserved. 8 Why does data type matter? 0 1 2 3 4 5 6 2013 2014 2015 2016 2017 One Two Three Four Quantitative variables make axes Categorical variables make “buckets” or headers Quantitative variables make… sequential and diverging color palettes with varying saturation Categorical variables make colors with different hues
3. 3. Missoula, MT – 30°F on January 10th Missoula, MT – 15°F on January 16th Is the temperature “half” of what it was last Friday?
4. 4. © 2018 Data Literacy. All rights reserved. 11 Starts with A Starts with B Starts with C Animals Sports Fruit AnimalsStarts with A Starts with A Starts with A Starts with B Starts with B Starts with B Starts with C Starts with C Starts with C Sports Fruit Animals Sports Fruit Animals Sports Fruit 🏀 🍎 🏏 🐻 😺 🍌 🍒 Learning About Reshaping Data with Emojis “Stacked” or “Record” FormatPivoted Format 🎯🐜
5. 5. The “Average” NFL Player… …is about 25 years old, just over 6'2" in height, weighs a little more than 244lbs and makes slightly less than \$1.5M in salary per year. Can you tell which distribution goes with which trait? Age SalaryWeight Height
6. 6. 61,316 tows
7. 7. What are the most common Makes that got towed?
8. 8. “Ford” “FORD” “FORF” “Forrrd”
9. 9. “Peterbilt” “Peterbelt” “Peterbutt” “Pete”
10. 10. “Mitsubishi” “Mitsubishit”
11. 11. “Burnt Car”
12. 12. Who needs spell check, anyway?
13. 13. What was the effect of cleaning the Make column?
14. 14. What was the effect of the grouping?
15. 15. In 1642, Abel Tasman was the first European to discover New Zealand. He mistakenly though the two islands were connected, and named the area between the Zeehaen’s Bight, after his ship In 1769, over a century later, James Cook was the first European to completely circumnavigate the pair of islands that make up the native home of the Māori people. He correctly noticed that there was a passage through, and the two land masses weren’t connected. The area between them is now knows as Cook’s Strait
16. 16. Ethics and Data Science by DJ Patil, Hilary Mason, Mike Loukides The 5 C’s: • Consent • Clarity • Consistence and Trust • Control and Transparency • Consequences Princeton Case Studies: Automated healthcare app, Dynamic sound identification, Optimizing schools, Law Enforcement ChatBots, Hiring by machine, Public sector data analytics https://aiethics.princeton.edu/case-studies/