????????????????3100 ???????????????? ???????????????????????????????????????????????????? ???????? ???? ???????????????????????????????????????? 3 ????????????????Assessment 3 InformationSubject Code: TECH3100Subject Name: Data Visualisation in RAssessment Title: Coding Assignment AnalysisAssessment Type: IndividualWord Count: 2000 Words

????????????????3100 ???????????????? ???????????????????????????????????????????????????? ???????? ???? ???????????????????????????????????????? 3 ????????????????Assessment 3 InformationSubject Code: TECH3100Subject Name: Data Visualisation in RAssessment Title: Coding Assignment AnalysisAssessment Type: IndividualWord Count: 2000 Words (+/-10%)Weighting: 40 %Total Marks: 40Submission: Via MyKBSDue Date:Week 13Your TaskThis assessment is to be completed individually. In TECH3100 Data Visualisation in R Assessment 3, you will evaluate your ability to apply and critically analyse visualisation techniques using the R language with the ggplot2 library.Assessment DescriptionFor this assessment, you will demonstrate and analyse the application of visualisation techniques using the R language with the ggplot2 library. Follow the instructions below to complete the assessment: Case Study Selection: Select a suitable case study that involves a complex data analysis scenario relevant to your field or area of interest. Ensure that the case study has diverse and rich data suitable for visualisation. Data Import and Preparation: Import the chosen dataset into R using appropriate functions or libraries. Conduct necessary data cleaning, preprocessing, and transformation steps to prepare the data for visualisation. Exploratory Data Visualisation: Apply the ggplot2 library to create a variety of visualisations that explore different aspects of the dataset. Utilise appropriate plot types, aesthetics, and statistical transformations to effectively represent and analyse the data. Design and Customisation: Demonstrate the design of visualisations that align with best practices and principles of effective data visualisation. Customise visualisations by modifying aesthetics, scales, themes, and annotations to enhance clarity and visual appeal. Analysis and Interpretation: Critically analyse the visualisations to identify patterns, trends, and relationships within the data. Interpret the insights gained from the visualisations and relate them to the case study context. Formulate data-driven recommendations or decisions based on the analysis and insights derived. R Code Documentation: Document your R code using comments to explain the purpose and functionality of each step in the analysis. Ensure that your code is well-structured, readable, and easily understandable. This assessment aims to achieve the following subject learning outcomes:LO3 Evaluate and apply visualisation techniques for data analytics.LO4 Design visualisations to support data-driven decision-making processes.Assessment InstructionsStudents must conduct research externally and included references in order to produce a well referenced assessment. You should use at least ten (10) sources of information and reference these in accordance with the Kaplan Harvard Referencing Style. These may include websites, social media sites, industry reports, census data, journal articles, and newspaper articles. These references should be presented as in-text citations and a referencing list at the end of your assessment (not included in the word limit). Wikipedia and other ‘popular’ sites are not to be used. Report: You must submit your report in Word document or in PDF format. R Code: Include the complete R code you used to perform the analysis. Ensure that the code is well-documented with comments. You must submit your R code in .r format extension. Any other formats will not be accepted. Please refer to the assessment marking guide to assist you in completing all the assessment criteria. Note: zipped files will not be accepted.Important Study InformationAcademic Integrity and Conduct Policyhttps://www.kbs.edu.au/admissions/forms-and-policiesKBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.Please read the policy to learn the answers to these questions: What is academic integrity and misconduct? What are the penalties for academic misconduct? How can I appeal my grade?Late submission of assignments (within the Assessment Policy)https://www.kbs.edu.au/admissions/forms-and-policiesLength Limits for AssessmentsPenalties may be applied for assessment submissions that exceed prescribed limits.Study AssistanceStudents may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Further details can be accessed at https://elearning.kbs.edu.au/course/view.php?id=1481Generative AI Traffic LightsPlease see the level of Generative AI that this assessment is Level 2 has been designed to accept:Traffic LightAmount of Generative Artificial Intelligence (Generative AI) usageEvidence RequiredThis assessment(✓)Level 1Prohibited:No Generative AI allowedThis assessment showcases your individual knowledge, skills and/or personal experiences in the absence of Generative AI support.The use of generative AI is prohibited for this assessment and may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment.Level 2Optional:You may use Generative AI for research and content generation that is appropriately referenced.See assessment instructions for detailsThis assessment allows you to engage with Generative AI as a means of expanding your understanding, creativity, and idea generation in the research phase of your assessment and to produce content that enhances your assessment. I.e., images. You do not have to use it.The use of Gen AI is optional for this assessment.Your collaboration with Generative AI must be clearly referenced just as you would reference any other resource type used. Click on the link below to learn how to reference Generative AI.https://library.kaplan.edu.au/referencing- other-sources/referencing-other-sources- generative-aiIn addition, you must include an appendix that documents your Generative AI collaboration including all prompts and responses used for the assessment.Unapproved use of generative AI as per assessment details during the content generation parts of your assessment may potentially resultin penalties for academic misconduct, including but not limited to a mark of zero for the assessment. Ensure you follow the specific assessment instructions in the section above.✓Level 3Compulsory:You must use Generative AI to complete your assessmentSee assessment instruction for detailsThis assessment fully integrates Generative AI, allowing you to harness the technology’s full potential in collaboration with your own expertise.Always check your assessment instructions carefully as there may still be limitations on what constitutes acceptable use, and these may be specific to each assessment.You will be taught how to use generative AI and assessed on its use.Your collaboration with Generative AI must be clearly referenced just as you would reference any other resource type used. Click on the link below to learn how to reference Generative AI.https://library.kaplan.edu.au/referencing- other-sources/referencing-other-sources- generative-aiIn addition, you must include an appendix that documents your Generative AI collaboration including all prompts and responses used for the assessment.Unapproved use of generative AI as per assessment details during the content generation parts of your assessment may potentially result in penalties for academic misconduct, including but not limited to a mark of zero for the assessment. Ensure you follow the specific assessment instructions in the section above.