The final project for the course is a technical blog post related to a data analysis project you will work on piecemeal over the course of the semester.
The project is very open ended. The objective is to demonstrate your skill in asking meaningful questions of your data and answering them with results of the data analysis using R / Rmarkdown, and that your proficiency in interpreting and presenting the results. The goal is not to conduct an exhaustive data analysis. The data analysis part should meet the following criteria:
1. Perform exploratory data analysis summarizing your data using descriptive statistics / summary statistics and visualizations relevant to your questions or ones that highlight some interesting insight.
2. Demonstrate at least two of the following techniques we have learned in class and that helps answer your question: PCA, hypothesis testing / confidence interval, regression analysis (linear /logistic)
The first task is to identify the dataset, understand the data and write questions you are planning to answer using that dataset. You may pick a data set from one of the resources mentioned on this webpage (Links to an external site.). The proposal should meet the following criteria:
1. Perform checks to determine quality of the data (missing values, outliers, etc.)
2. Proposal on what questions you are interested in answering from the data
3. Initial visualizations and if required transform to get the data ready
A good reference for ideas on questions and EDA in general: https://r4ds.had.co.nz/exploratory-data-analysis.html
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