perform univariate analysis on the dataset using either R, Python, or Rapid Miner Studio. Use descriptive and meaningful comments in the code or process file as documentation. This assignment is in two parts. The first part is about the exploratory data analysis performed on the selected dataset. The second part discusses the steps you took during the exploratory data analysis and insights obtained in the process.
Part 1:
Create a set of research questions and corresponding hypotheses couplets to guide your analysis.
Select appropriate univariate methods to describe patterns found in univariate data and perform univariate analysis on the selected dataset.
Create appropriate annotated visualizations for each part of the analysis.
Part 2:
Compare and contrast different univariate methods that can be used in exploratory data analysis.
Describe the process you used to select an appropriate univariate method to describe patterns in the selected dataset. Justify the univariate method selected for your analysis.
Embed the annotated visualizations created for each part of the univariate analysis.
Describe statistical findings and insights obtained as a result and subsequent actions that should be taken with the dataset.
Length: 5 to 7-page paper, not including title and reference pages, and screenshots of visualizations provided in Appendix. Attachment – .ipynb file (Jupyter Notebook) or .r file (R) or .rmp file (Rapid Miner Studio).
References: Include a minimum of 2 scholarly references.
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