Define visual analytics:
The science of analytical reasoning facilitated by INTERACTIVE visual interfaces
What do you want to discover with visualizations when doing visual analytics? (4)
- Data structure
- Parameters
- Relationships among variables
- Properties of the data
List the tasks of exploratory analysis: (6)
- Making sense of data
- Discover facts
- Reveal patterns, outliers and trends
- Find correlations
- Reveal rankings
- Perform multivariate analysis
What is an important feature of an exploratory analysis?
Interaction
Which type of statistics we use to make sense of data?
Descriptive statistics
In descriptive statistics which measures of central tendency do we use? (3)
Mean, median, mode
In descriptive statistics which measures of dispersion do we use? (5)
range, percentile, variance, standard deviation, quantiles
Which visual patterns do we look for with dot representations? (5)
- trends
- concentration
- clusters
- gaps
- outliers
Which visual patterns we look for with line representations? (5)
- increases, decreases and stationarity
- curves
- repetitions
- interactions
- covariation
Which types of visualizations are the most suitable to look for correlations?
- Scatterplot
- Scatterplot matrix
- Heatmap
List techniques to perform cluster analysis: (2)
- K-means
2. Density-based
Which are the best visualizations to show part-to-whole? (4)
- Stacked bar chart
- Stacked area chart
- Bar chart, with cumulative percentage line (see chapter 8 slide 38)
- Waffle chart
- Pie chart XD
What should we pay attention to when ranking?
Look for proportions over absolute values
Which are the best suited visualizations to perform multivariate analysis? (5)
- Composed axis
- Parallel coordinates
- Scatterplot matrices
- Tablelens
- Radar charts
What are we looking for with interaction? (3)
- Changing the type of visualization
- Selection, filter, focus, getting details
- Transforming data
