Tidy Data is often not the most intuitive way for students to initially collect and enter data, but fortunately it can often be simple to convert. Check out the blogpost below to brush up on the process. https://lnkd.in/ewDbUDdx
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Interesting fun fact I've learned while creating fake data for my data cleaning course: You can chain multiple `write_*()` functions from the {readr} package. All of these invisibly return the original data. So you can just pass that invisible output to the next write function. That way, you can save the same data set to a myriad of formats quick & easy. Proably a rare use case but for me it was just the right thing to create a bunch of different file formats for teaching.
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Students must be able to collect, organize, understand, and communicate data to meet the demands of modern society. One instructional resource that supports students with this immediate need is Data Talks—short activities that expose students to data and allow them to interpret data visualizations. A Data Talk offers students a data visualization, invites them to make observations and ask questions, and helps them to develop the critical-thinking skills they need to interpret the data surrounding them every day. Learn more about the importance of incorporating data into everyday instruction and the key features of a Great Minds Data Talk here: https://ow.ly/9G3250RjY4t #Educators #DataScience
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How we support a student as they begin to work with their own data. Cool features are great, but what exactly can a tool assist with at the data import and preparation stages? https://lnkd.in/dbTgdqbA #DataScience #TeachingStats #DataLiteracy
Scaffolding for learning to prepare your own data — DataClassroom
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Ever gotten tripped up on tree based data structures? The data structure that I spend the most time teaching are tree based data structures. I've created a begineer friendly post that breaks down where they're used, how they're used and real world examples. Link is in the first comment below 👇
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Looking for real world projects can help preparing for the challenges we face in our daily work.
Clean data, always ready to use, nice Excel sheets.. that is not reality! I understand it helps to learn data analysis, but students are not being prepared for the real world they will have to work in. Also, there is a huge need for creativity in data engineering, in extracting data from complicated systems and preparing it for usage. You learn that by doing. Universities should address this gap and prepare their students.
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Finding, Sorting, & Filtering Data in Microsoft Excel https://lnkd.in/dYpn8pyi
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Struggling to explain data formatting for analysis? Time to learn about Tidy Data, term coined by @HadleyWickham. It will change your life! Read more: https://lnkd.in/ewDbUDdx #DataScience #TeachingStats #DataLiteracy
Do you know how to make a Tidy Data table? Here's how. — DataClassroom
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Is there any tools for in data analysis to make work easy??? Yes, know the tools for data analysis and machine learning. We offer course training along with 100% placement assistance. Enroll Now!!! #learnovita #dataanalysistraining #machinelearningtools #machinelearningalgorithms
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Preparing Data for Analysis with Microsoft Excel
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Educational Data Analytics technologies are now considered as useful to overcome practical barriers for sustainable and effective data-driven decision making in teaching and learning. https://buff.ly/497S5XX #EducationalDataAnalytics #Rellie #RellieLearn
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