Author
Released
4/17/2019- The ROI of data fluency
- Data ethics
- Preparing data
- Assessing the quality of data
- Visualizing data with bar, pie, and line charts
- Describing variability with the variance and standard deviation
- Describing associations with correlations
Skill Level Beginner
Duration
Views
- [Barton] This is a transformational time in our history, the data revolution has produced some jaw dropping advances in technology, medicine, commerce, and so many other fields. But data doesn't have to be industrial scale to be useful. It turns out that entrepreneurs, startups, and small businesses can get significant insights and jump starts from basic analysis of even small data sets. This is where data fluency comes in. I'm Barton Poulson and in this brief course we'll explore the fundamental concepts of data fluency or the ability to work with data to extract insights, get new passive inquiry, and find suggestions for next steps.
We'll explore the different principles and techniques of data fluency in a software agnostic presentation that focuses on the goals of common procedures and how to get insights from them. We'll cover some useful methods for preparing data, exploring with quick visualizations, and getting common descriptive statistics like the mean and the standard deviation. And we'll make specific suggestions on how you can find value in any data set. Because this is a nontechnical overview anyone with an interest in informed decision making regardless of their technical background can get a better understanding of the ways that data can guide them to do the things that are important to them, and to do them more effectively and more efficiently.
So let's get started with Data Fluency: Exploring and Describing Data.
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Introduction
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1. Think with Data
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The meaning of data fluency6m 40s
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Data fluency is for everyone2m 27s
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Data fluency in practice6m 58s
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Think about causes5m 1s
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How to develop data fluency4m 26s
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Data-driven decision-making6m 35s
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Put data in context6m 58s
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2. Prepare Data
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Data ethics7m 41s
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Use in-house data4m 37s
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Use open data6m 59s
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Gather new data6m 28s
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Use third-party data4m 17s
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Assess the quality of data4m 47s
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Adapt data: Sums and means6m 27s
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Adapt data: Rates3m 50s
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Adapt data: Ratios4m 10s
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Adjust ratios in practice3m 42s
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3. Explore Data
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Bar charts6m 51s
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Grouped bar charts6m 35s
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Pie charts8m 4s
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Dot plots5m 18s
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Box plots6m 49s
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Histograms4m 37s
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Line charts8m 23s
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Sparklines5m 2s
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Scatterplots8m 22s
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4. Describe Data
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Numerical descriptions1m 24s
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Describe measures of center7m 30s
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Rescale data with z-scores4m 11s
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Interpret z-scores5m 21s
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Interpret effect sizes4m 27s
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Conclusion
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Next steps6m 34s
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Video: Gather greater insight and make better decisions with your data