Data Visualization Level 2 Quiz

Graphical or pictorial representation of data using graphs and charts to show variations or relationships between variables.

Show variations and relationships between data variables.

Data visualization combines artistic design with scientific accuracy to accurately portray data.

Visual representation of data where numerical differences are correctly reflected in visual sizes.

Technically correct data visualization, but has poor aesthetics, distracting colors or fonts.

Visual representation that is unclear, confusing, overly complex, or misleading due to perceptual issues.

Visually incorrect as there are errors in the underlying mathematics or calculations producing the data.

The various aspects (position, shape, size, color) of graphical elements used to represent data.

Describing where the graphical element is located using coordinates (e.g., x, y).

Describes the form of a graphical element (e.g., a bar, a line).

Describes the dimensions or magnitude of a graphical element.

Describes hues, shades, or tints used for distinguishing graphical elements.

Data values with arbitrarily fine intermediates between any two values.

Data values that do not have arbitrarily fine intermediates.

Numerical data that can be measured and represented quantitatively.

Categorical data that describes qualities or characteristics.

Variables holding qualitative data with different categories.

Categories within a factor.

Properties of visual elements used to represent data, like position, shape, size, color.

A mapping between data values and aesthetic values (e.g., mapping numbers to colors or positions on a graph).

A scale where each data value corresponds to exactly one aesthetic value, and vice versa. This prevents ambiguity in the visualization.

A scale that maps data values to positions on an axis (e.g., x or y axis).

A scale that maps data values to different shapes.

A scale that maps data values to different colors.

Data that can only take on specific, distinct values (e.g., categories).

A categorical variable whose categories have a natural order (e.g., months of the year).

A categorical variable whose categories do not have a natural order (e.g., locations).

A plot that displays data points connected by lines, often to show trends over time or other continuous variables.

A scale that maps data values to different sizes of graphical elements, like data points.

Visualizing complex data using multiple simultaneous scales (e.g., x-axis, y-axis, color, size, shape).

Data with values that can take on any intermediate value between two points; examples include displacement, fuel efficiency, power, and weight.

Data that can only take on specific, separate values, or data with categories that have a natural order, as in the number of cylinders of an engine.

A 2D coordinate system (like a graph) where each point is located by its x and y values.

Axes in a graph where values can be any number within a range.

The units used to measure data (e.g., kilometers, degrees Celsius).

The ratio of the width to the height of a graph.

If x and y axes have the same units, the spacing between grid lines should be equal.

Representing data in a visual format, typically using a graph.