Final answer:
A report using R should begin with well-defined questions, focusing on insights that emerge from data analysis. Your analytical report must include a thesis, data analysis, conclusions, and integrate visuals like graphs and charts.
Step-by-step explanation:
When conducting an exploratory data analysis using R to create a report, it is paramount to start by formulating questions which the report will address. Here are twelve questions to consider, focusing on insights from the data:
- What patterns emerge from the distribution of key variables?
- Are there any unexpected correlations between different variables?
- How do outliers impact the overall trends in the data?
- Does a time series analysis reveal any recurring patterns or seasonality?
- What insights can be derived from clustering or segmentation of the data?
- How does data from one subset compare to the overall dataset?
- Are there any geographical trends apparent when mapping the data?
- What are the descriptive statistics, such as mean and median, of the critical variables?
- How are categorical variables distributed throughout the dataset?
- Which variables significantly influence the outcome of the dependent variable?
- What hypotheses can be formulated based on preliminary data exploration?
- How does the distribution of variables differ when comparing groups within the data?
As stated in the assignment, your analytical report must present and analyze this information, drawing conclusions and possibly comparing and contrasting data points. Remember to draft a thesis that governs the report's narrative and to support it with evidence from various sources.
Visuals are also a crucial component of an effective analytical report. Utilize a variety of visuals such as graphs, charts, and maps to enhance the comprehensibility of your analysis. Ensuring that these visuals are well-integrated with the written content will help the reader to understand and engage with your findings.