Midterm Project

Due Sunday, October 26th, 2024 by 11:59pm Pacific Time.

Learning Objective: To apply the skills learned in PM 566 (through Week 6) by analyzing and interpreting a dataset of your choice.

Narrative: As we have discussed in class, the practice of data science requires both quantitative skills and qualitative knowledge of the domain from which the data was collected. The first step in any data analysis is to have a dataset for which you have formulated an interesting question. If you do not have a dataset to work with, you may choose one from our list of suggestions. With your dataset, formulate a clear and concise question to answer and conduct data wrangling, exploratory data analysis, and data visualization to explore/answer this question.

Deliverable: A written report generated in Quarto (HTML or PDF) with embedded tables and figures that is submitted to a project-specific GitHub repository that you create. The report should have the following sections:

• Introduction - provide background on your dataset and formulated question
• Data Preparation - how and where the data were acquired, how you cleaned and wrangled the data
• Exploratory Analysis - dataset characteristics, variables included, distribution of key variables
• Preliminary Results - analysis of the primary research question and any subsequent follow-up questions, including summary statistics in tabular form and publication-quality figures (look at the kable() function from knitr for making nice tables)
• a brief Conclusion - summary of what you found in the data

In your report, please do not include any unformatted text output (e.g. output from head(), str(), print(), etc.). You should summarize these aspects of your data within the text, figures, and/or tables.

Note that you cannot use the same dataset on both the Midterm and Final. So if you came into this class with a dataset that you wanted to analyze, you may want to save that for later.