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In this course, you will learn :
- 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
Syllabus :
1. Think with Data
- The meaning of data fluency
- Data fluency is for everyone
- Data fluency in practice
- Make intuitive thinking explicit
- Think about causes
- How to develop data fluency
- Data-driven decision-making
- ROI and the 80/20 rule for data fluency
- Put data in context
2. Prepare Data
- Data ethics
- Use in-house data
- Use open data
- Gather new data
- Use third-party data
- Assess the quality of data
- Assess the generalizability of data
- Assess the meaning of data
- Assess the ambiguities in data
- Adapt data: Coding text
- Adapt data: Sums and means
- Adapt data: Rates
- Adapt data: Ratios
- Adjust ratios in practice
3. Explore Data
- Visual primacy: The importance of starting with pictures
- Bar charts
- Grouped bar charts
- Pie charts
- Dot plots
- Box plots
- Histograms
- Line charts
- Sparklines
- Scatterplots
4. Describe Data
- Numerical descriptions
- Describe measures of center
- Describe variability with the range and interquartile range (IQR)
- Describe variability with the variance and standard deviation
- Rescale data with z-scores
- Interpret z-scores
- Describe group differences with effect sizes
- Interpret effect sizes
- Predict scores with regression
- Describe associations with correlations
- Effect size for correlation and regression
