Publications by Denise Adele Chua
IS415-Hands-on Exercise 8 (Supplement)
1.0 Overview This is an exercise to gain experience using appropriate R functions to perform spatial point patter analysis. The case study aims to discover the spatial point processes of childecare centres in Singapore. The research question we aim to answer: - are the childcare centre centres in Singapore randomly distributed throughout the coun...
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R4DSA: Hands-on Exercise 1-Working with R Data Objects
1 R Data Types and Structures R has a wide variety of objects for holding data, including scalars, vectors, matrices, arrays, data frames, and lists. They differ in terms of the type of data they can hold, how they’re created, their structural complexity, and the notation used to identify and access individual elements. 1.1 Basic data types o...
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IS415 Hands-on Exercise 3: Choropleth Mapping with R
1.0 Overview Choropleth mapping involves the symbolization of enumeration units, such as countries, provinces, states, counties or census units, using area patterns or graduated colors. For example, a social scientist may need to use a choropleth map to portray the spatial distribution of aged population of Singapore by Master Plan 2014 Subzone B...
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IS415-Hands-on Exercise 2: Geospatial Data Wrangling in R
1 Overview In this hands-on exercise, you will learn how to handle geospatial data in R by using appropriate R packages. 1.1 Learning Outcome By the end of this hands-on exercise, you should aquire the following competencies: import geospatial data by using appropriate functions of sf packages, import geospatial data as R spatial object type by...
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Choropleth Mapping with R
1.0 Overview Choropleth mapping involves the symbolization of enumeration units, such as countries, provinces, states, counties or census units, using area patterns or graduated colors. For example, a social scientist may need to use a choropleth map to portray the spatial distribution of aged population of Singapore by Master Plan 2014 Subzone B...
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Mosaic Plot Visualisation
Overview In this hands-on exercise, you will learn how to visualising and analysing multivariable categorical data using mosaic plot data visualisation technique. Installing and Launching R Packages For this exercise, the vcd package of R will be used. You are required to install vdc package if is has yet to be installed in your computer. You ar...
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Visualising Correlation Matrix
1.0 Overview Correlation coefficient is a popular statistic that use to measure the type and strength of the relationship between two variables. The values of a correlation coefficient ranges between -1.0 and 1.0. A correlation coefficient of 1 shows a perfect linear relationship between the two variables, while a -1.0 shows a perfect inverse rel...
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Creating Ternary Plot with R
1.0 Overview Ternary plots are a way of displaying the distribution and variability of three-part compositional data. (For example, the proportion of aged, economy active and young population or sand, silt, and clay in soil.) It’s display is a triangle with sides scaled from 0 to 1. Each side represents one of the three components. A point is p...
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Heatmap Visualisation with R
1.0 Overview Heatmaps visualise data through variations in colouring. When applied to a tabular format, heatmaps are useful for cross-examining multivariate data, through placing variables in the columns and observation (or records) in rowa and colouring the cells within the table. Heatmaps are good for showing variance across multiple variables,...
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Creating Parallel Coordinate Plot
1.0 Overview Parallel coordinates plot is a data visualisation specially designed for visualising and analysing multivariate, numerical data. It is ideal for comparing multiple variables together and seeing the relationships between them. For example, the variables contribute to Happyness Index. In this hands-on exercise, you will learn how to pl...
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