- Define visualization.
- Explain the importance of humans in the visualization process.
- Explain why human vision is particularly well-suited for information transfer.
- Give an example of a visualization idiom.
- Explain why it is best to consider multiple alternatives for vis before selecting a solution.
- Explain at a high-level the "why-what-how" framework for analyzing visualization use.
- Differentiate between Seaborn, Vega-Lite, D3, and Tableau and describe the type of tasks for which each tool might be most appropriate.
- Distinguish among the four basic dataset types.
- Distinguish among the five core data types.
- Distinguish between categorical and ordered attributes.
- Distinguish between ordinal and quantitative attributes.
- Explain why understanding the dataset and data types and semantics matter for designing effective visualizations.
- Distinguish between scientific vis and information vis in terms of how spatial data is used.
- Explain the difference between a flat table and a multidimensional table.
- Explain some of the complexities of dealing with temporal data.
- Identify two tools for cleaning data.
- Explain how marks and channels are related.
- Distinguish between the identity channel type and the magnitude channel type and indicate which channels belong to each type.
- Distinguish between the principles of expressiveness and effectiveness in visual encoding.
- List the channels for ordered attributes in order from most effective to least effective.
- List the channels for categorical attributes in order from most effective to least effective.
- Describe the effects of accuracy, discriminability, separability, popout (preattentive processing), and grouping and give one example that illustrates each.
- Explain the implication of Stevens' Law for visualizations.
- Explain the implication of Weber's Law for visualizations.
- Explain why the arrange design choice is the most crucial visual encoding choice.
- Explain how the concepts of express, separate, order, and align all relate to arranging tabular data.
- For each idiom example in the text (from scatterplot to normalized stacked bar chart), identify the "what: data" properties of the idiom.
- For each idiom example in the text, identify the "how: encode" properties of the idiom.
- For each idiom example in the text, identify the "why: task" properties of the idiom.
- For each idiom example in the text, identify the "scale" properties of the idiom.
- Differentiate between line charts and bar charts and explain when each is appropriate
- Explain some of the disadvantages of pie charts.
- Explain how a radial layout maps to a rectilinear layout.
- Given a particular dataset and task, suggest an idiom and explain why it might be appropriate
- Identify a visualization where an inappropriate arrange design choice was made and explain why the choice was inappropriate.
- Describe the components of color.
- Describe the three main types of colormaps.
- Explain the importance choosing an appropriate colormap.
- Given a set of data and a task, determine an appropriate colormap.
- Identify an inappropriate use of a colormap and suggest a more appropriate one.
- Explain why rainbow colormaps should only be used with great care.
- For the visual channels other than color, identify which are magnitude and which are identity channels.
- Describe how the arrange design choice is different with spatial data as opposed to tabular data.
- Describe a choropleth map.
- Explain potential difficulties with the use of 3D visualization.
- Identify situations in which the use of 3D visualization would be appropriate.
- Explain why "eyes beat memory".
- Explain what happens when people experience cognitive load.
- Define change blindness.
- Explain the tradeoff between resolution and immersion.
- Explain the Shneiderman mantra "overview first, zoom and filter, details on demand".
- Explain the alternate concept of "search, show context, expand on demand" and identify in what situations it may be more appropriate than the Shneiderman mantra.
- Explain the importance of the design slogan "get it right in black and white".
- Explain the need to reduce data, both in terms of number of items and number of attributes.
- Explain the difference between filtering and aggregation and the purposes of each.
- Identify instances of scented widgets, as opposed to standard filtering widgets.
- Contrast histograms with bar charts.
- Explain the importance of binwidth in a histogram.
- Describe the components of a boxplot.
- List the three steps in the iterative cycle of EDA.
- Explain the concept of covariation.
- Name some questions to ask about patterns found in data.
- Given a dataset, generate questions aimed at examining correlation and understanding underlying patterns in the data.
- List the seven genres of narrative visualization.
- Describe the Martini glass structure of narrative visualization.
- Describe a stepper in an interactive visualization.
- Describe how narrative visualization and presentation visualization differ from exploratory/analysis visualization, especially in terms of tools and approaches.
- Explain the concept of visual literacy.
- List 6 tips for spotting misinformation.
- Demonstrate the use of Fermi estimation.
- Explain confirmation bias.
- List 10 suggestions for spotting misinformation online.
- Given a misleading visualization, identify the misleading elements and suggest how the visualization could be improved.
- Explain the importance and usefulness of faceting data across multiple views.
- Contrast the two major approaches to faceting information.
- Describe the four major design choices for juxtaposed views.
- Explain the concept of linked highlighting.
- Describe the three alternatives for sharing data between two juxtaposed views.
- Contrast the use of small multiples with a grouped bar chart.
- Given a multiform visualization, identify the ways in which the data was split into multiple views and the design choices that were made.
- Describe why changing a view might aid in understanding a dataset.
- Explain why order can make such an impact in understanding.
- Describe some of the design choices that can be made with selection.
- Explain the difference between selection and highlighting.
- Given an interactive visualization, identify the interaction idioms used.