Educational guide School of Engineering |
english |
Computer Security Engineering and Artificial Intelligence (2016) |
Subjects |
INTERACTIVE AND VISUALISATION SYSTEMS |
Contents |
IDENTIFYING DATA | 2021_22 |
Subject | INTERACTIVE AND VISUALISATION SYSTEMS | Code | 17685206 | |||||
Study programme |
|
Cycle | 2nd | |||||
Descriptors | Credits | Type | Year | Period | ||||
3 | Optional | 2Q |
Competences | Learning outcomes | Contents |
Planning | Methodologies | Personalized attention |
Assessment | Sources of information | Recommendations |
Topic | Sub-topic |
Introduction to Data Visualization | What is Data Visualization? Why is Data Visualization so important? What is Data Visualization useful for? The problem of Data Visualization Types of Data Visualization |
Graphical Perception | The elementary perceptual tasks |
Graphical Excellence, Integrity and Sophistication | The principles of Graphical Excellence The principles of Graphical Integrity Graphical Distortion The lie factor The principles of Graphical Sophistication The data-ink ratio Data density Proportion and scale |
Statistical traps | Summary statistics Quoting data out of context Incorrect normalization of the data Jumping to the wrong conclusions The Simpson's paradox |
Plots | Types of plots How to choose the type of plot according to your data and purpose Common mistakes with plots |
Introduction to R | The basics of R Data Types in R Data Utilities in R |
Introduction to ggplot2 | The Grammar of Graphics The components of the Grammar of Graphics |
Mastering ggplot: the grammar | Geometries Datasets and mappings Statistical transformations Position Adjustments Scales Coordinate Systems Themes Facets |
Mastering ggplot: the plots | The line plot family The scatter plot family The bar plot family Displaying distributions I Displaying distributions II Maps Custom Plots |