• COMM1190 R数据分析 data analysis

    COMM1190 Assessment 1: Individual Report
    Brief
    Australia’s Globe Trotters, a travel booking company that re-sells international and domestic flights, recently conducted a survey to gauge consumer satisfaction with their website. The raw data from this survey have been compiled and are provided in the file (websat_raw.xls). An intern in the Customer Insights Team was tasked with analysing this data and reporting back to the Manager of the Customer Insights Team.
    The Manager provided general guidelines for the report. In her email instructions to the intern, she stated:
    "I am looking for a brief overview of the consumer survey results, focusing on (1) the level of satisfaction consumers have with our website; (2) 2-3 discernible patterns or trends that might indicate why consumers are satisfied or dissatisfied with our website for future investigation; (3) a brief summary of any anomalies or limitations of the data."
    The intern's memo to the Manager is included in Appendix A, and the data dictionary is in Appendix B. The manager was furious with the submitted memo by the intern and as a result of its poor professional standards, lost faith in the credibility of the report’s findings. The manager has asked you to re-do the report to meet their instructions.
    She also insists that the entire analysis is done in R so that, if necessary, a senior analyst can quickly double-check the report.
    Task
    Using R, you will explore a dataset and create exploratory visualisations to address the manager’s queries. Clearly, concisely and professionally communicate your results and conclusions in a 750-word memo. In addition to submitting your memo, you will provide a two-part appendix.
    Appendix A outlines the end-to-end process of your data analysis. Appendix A, which has a 500-word limit, should detail your approach to the problem, including the methods used to select and clean the data, any data exploration or visualisation techniques, and how you arrived at your conclusions. You should also include any graphs, tables, or summary statistics that helped guide your analysis. The technical appendix should be written clearly and concisely so that another analyst can understand your approach to the problem and replicate your findings.
    Appendix B is a printout or screenshots of your data exploration and R-code that can re-create the exploratory data visualisations associated with the graphs presented in the one-page report. Overall, the assessment is designed to help you develop your R and data communication skills. Appendix B does not have a word count.
    Elements to Include the Memo:
    • Introduction: Provide a brief overview of the topic, including the purpose and
    context of the report.
    • Key Findings: Use charts, graphs, or other visual elements to highlight the
    most important findings from the research.
    • Conclusion: Summarize the main takeaways from the report, addressing the
    manager’s requirements. If applicable, include a call to action.
    Guidance on Data Analysis:
    Note: the original memo, data, and data dictionary will be provided to you separately.
    • It is important to emphasise that there is no single correct answer to the
    assignment. The data set involves many different dimensions for you to explore, and some aspects and dimensions of the data are likely to be more useful than others. Therefore, it is important that you systematically explore the different variables in the dataset before starting your assignment.
    • Although you may create many graphs for your assessment (e.g., histograms to better understand the data), you only want to include figures that support your main findings.
    • Remember that your data exploration and visualisations should well support your conclusions. You should also outline key assumptions or limitations in your datadriven conclusions.
    Tips for the Technical Appendix:
    • Explain your methodology: Describe the methods you used to select and clean the data, including any pre-processing or data-wrangling techniques you used. Be sure to explain why you made your choices and how they relate to the problem you were trying to solve.
    • Detail your analysis process: Describe how you analysed the data, including any statistical techniques you used. Explain how you arrived at your conclusions, including any graphs, tables, or summary statistics that helped guide your analysis.
    • Include visuals: Include relevant graphs, charts, or other visual aids in your
    technical appendix to help illustrate your points and make your analysis more
    accessible.
    • Be transparent about any limitations: Be transparent about any limitations of your analysis, such as missing data or sample size limitations, and explain how you accounted for these limitations.
    • Keep it concise: While it's important to be specific and thorough, it's also
    important to be concise since you only have 500 words. To ensure that you
    maximize your space, take time to edit and revise your Appendix.
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  • 原文地址：https://blog.csdn.net/zhuyu0206girl/article/details/136363149