TAILIEUCHUNG - Lecture Data visualization - Chapter 6

This chapter presents the following content: Quantitative messages related to data visualization, characteristics of effective graphical display. | Lecture 06 Recap Quantitative Messages related to Data Visualization Characteristics of Effective Graphical Display Visual perception and Data Visualization A human can distinguish differences in line length, shape orientation, and color (hue) readily without significant processing effort These are referred to as "pre-attentive attributes" For example, it may require significant time and effort ("attentive processing") to identify the number of times the digit "5" appears in a series of numbers; but if that digit is different in size, orientation, or color, instances of the digit can be noted quickly through pre-attentive processing Continued . Effective graphics take advantage of pre-attentive processing and attributes and the relative strength of these attributes For example, since humans can more easily process differences in line length than surface area, it may be more effective to use a bar chart rather than pie charts Types of Information Display Two primary types Tables Graphs Tables A table contains quantitative data organized into rows and columns with categorical labels It is primarily used to look up specific values For example: a table might have categorical column labels representing the name (a qualitative variable) and age (a quantitative variable), with each row of data representing one person (the sampled experimental unit or category subdivision) Graphs A graph is primarily used to show relationships among data and portrays values encoded as visual objects ., lines, bars, or points Numerical values are displayed within an area delineated by one or more axes These axes provide scales (quantitative and categorical) used to label and assign values to the visual objects Many graphs are also referred to as charts Examples of Diagrams used for Data Visualization Bar-Chart Visual Dimensions length/count category color Histogram Visual Dimensions bin limits count/length color Scatterplot Visual Dimensions x position y position symbol/glyph color size

• Cơ sở dữ liệu
• Data visualization
• Lecture Data visualization
• Data modeling
• Database users
• Database systems
• Relational databases
• Lecture note Data visualization
• Data structures
• Data Visualization with C
• Data visualization with matlab
• Effective graphical display