Reference no: EM133925613
Data Visualisation in R
Assessment - Business Decision Case Study
Task
Propose your own business decision case study
This should be original and up to date. Try to place the case study in the context of an organisation you work for or have worked for. If this is not feasible you can imagine you work, or say you'd like to work, for some business. The size of the business doesn't matter, it could be you own web-based business, a grocery store, an airline, an environmental protection agency, or a government department. The business decision might be around adapting to increasing popularity of electric vehicles, or initiatives to reduce road traffic accidents, or changing prices of coffee beans, or adjusting to tariffs, or environmental issues, and so one. Look at articles in the financial sections of newspapers or news websites.
Identify suitable data
Comparisons with other organisations or from last year. Annual reports are a potential source of information. This assessment is, in part, about your ability to draw graphs using R software. Do not reproduce published graphs. If they are relevant, you could read approximate numerical values off the graph and redraw it using R.
This assessment is to be completed individually. In this assessment, you will evaluate your ability to apply and critically analyse visualisation techniques using the R language with the ggplot2 library.
Learning outcome 1: Evaluate and apply visualisation techniques for data analytics.
Learning outcome 2: Design visualisations to support data-driven decision-making processes.
Assessment Description
For this assessment, you will demonstrate and analyse the application of visualisation techniques using the R language with the ggplot2 library. You are asked to give a presentation using PowerPoint, and to write a report.
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. Get expert-level assistance in any subject with our assignment help services.
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.
Assessment Instructions
Students must conduct research externally and included references, in the Kaplan Harvard style, to produce a well-documented report. References may include websites, social media sites, industry reports, census data, journal articles, and newspaper articles. References should be presented as in-text citations with a reference list at the end of your report (not included in the word limit). For Web based resources you must give the url and date accessed. The date accessed is essential because web resources are sometimes removed without being archived.
The time available for your presentation will depend on the class size and will be set by your facilitator. Focus on your case study - what is the aim of the analysis and how have you met this aim. Use graphics throughout your presentation. You are not expected to justify your choice of graphics or explain how you draw them in your presentation.
Presentation: Powerpoint in class
Report: You must submit your report in Word document.
R Code: Include the complete R code you used to perform the analysis, together with the data files. Ensure that the code is well-documented with comments.
a) You must submit your R code in .r format extension, and the data files in a format that is read directly by your R code. Any other formats will not be accepted.