Please carefully read the statements below and check each box if you agree with the declaration. If you do not check all boxes, your assignment will not be marked. If you make a false declaration on any of these points, you may be investigated for academic misconduct. Students found to have breached academic integrity may receive official warnings and/or serious academic penalties. Please read more about academic integrity here. If you are unsure about any of these points or feel your assessment might breach academic integrity, please contact your course coordinator for support. It is important that you DO NOT submit any assessment until you can complete the declaration truthfully.
By checking the boxes below, I declare the following:
I have not impersonated, or allowed myself to be impersonated by, any person for the purposes of this assessment
This assessment is my original work and no part of it has been copied from any other source except where due acknowledgement is made.
No part of this assessment has been written for me by any other person except where such collaboration has been authorised by the lecturer/teacher concerned.
Where this work is being submitted for individual assessment, I declare that it is my original work and that no part has been contributed by, produced by or in conjunction with another student.
I give permission for my assessment response to be reproduced, communicated compared and archived for the purposes of detecting plagiarism.
I give permission for a copy of my assessment to be retained by the university for review and comparison, including review by external examiners.
I understand that:
Plagiarism is the presentation of the work, idea or creation of another person as though it is your own. It is a form of cheating and is a very serious academic offence that may lead to exclusion from the University. Plagiarised material can be drawn from, and presented in, written, graphic and visual form, including electronic data and oral presentations. Plagiarism occurs when the origin of the material used is not appropriately cited.
Plagiarism includes the act of assisting or allowing another person to plagiarise or to copy my work.
I agree and acknowledge that:
I have read and understood the Declaration and Statement of Authorship above.
If I do not agree to the Declaration and Statement of Authorship in this context and all boxes are not checked, the assessment outcome is not valid for assessment purposes and will not be included in my final result for this course.
The original data visualisation selected for the assignment was as follows:
library(knitr)
include_graphics(C:_ Job mobility by state and territory.jpeg)
The objective and audience of the original data visualisation chosen can be summarised as follows:
Objective
The aim of the data visualization is to illustrate the fluctuation in job changes across various states and territories in Australia.
Audience
Intended audiences for this data visualisation could include human resource professionals, labor market analysts, career counselors, job coaches, researchers and academics, business owners and government agencies and policymakers
The visualisation chosen had the following three main issues:
Complexity in representation: The visualization employs numerous grouped barplots and colors, resulting in a cluttered display that can confuse viewers. With too many categories or subgroups, this complexity makes it challenging for viewers to compare data both within and between groups effectively.
Lack of trend analysis: The visualization fails to incorporate trend analysis, which could provide valuable insights into the direction and magnitude of job changes over time. Without trend analysis, viewers may struggle to identify long-term patterns or changes in employment dynamics.
Lack of color differentiation: The use of similar colors across different years can cause visual overload, making it difficult for viewers to discern and compare data points. For instance, the use of similar shades of blue for different years can lead to confusion and impede the viewer’s ability to extract meaningful insights from the visualization.
The following code was used to fix the issues identified in the original.
library(ggplot2)
data <- data.frame( State = c(“NSW”, “Vic”, “Qld”, “SA”, “WA”, “Tas”, “NT”, “ACT”), Feb_20 = c(7.8, 8.8, 7.8, 8.1, 8.1, 7.7, 7.7, 9.2), Feb_21 = c(6.9, 7.1, 7.8, 6.8, 9.3, 8.8, 8.7, 10.2), Feb_22 = c(8.2, 10.1, 9.7, 8.7, 11.3, 8.9, 11, 13.3), Feb_23 = c(9.1, 9.2, 10, 9, 10.1, 10.3, 9.7, 12.5) )
data_melted <- reshape2::melt(data, id.vars = “State”, variable.name = “Year”, value.name = “Percentage”)
ggplot(data_melted, aes(x = as.factor(Year), y = Percentage, color = State, group = State)) + geom_line(size = 1.5) + labs(title = “Job Mobility by State and Territory”, y = “Percentage of job changes each year”, x = “Year”, color = “State”, caption = “Source: Australian Bureau of Statistics, Job mobility February 2023”) + theme_minimal() + theme(axis.text.x = element_text(angle = 45, hjust = 1))
The reference to the original data visualisation choose, the data source(s) used for the reconstruction and any other sources used for this assignment are as follows:
Job mobility, February 2023 | Australian Bureau of Statistics. (2023, June 30). Www.abs.gov.au. https://www.abs.gov.au/statistics/labour/jobs/job-mobility/feb-2023