Week 1 Assignment

Introduction

I’m very curious about the field of pharmaceutical research and clinical trials and I am wondering about what it would be like to work at a company like Genentech or Gilead Sciences after graduation.

For this first assignment, I want to analyze a clinical dataset focused on patient demographic and health-related attributes aimed at predicting the risk of hypertension. The raw data source can be accessed directly here: Kaggle Hypertension Risk Dataset.

Business & Data Science Question

• Business Question: How does patient demographic and health-related attributes relate to elevated resting blood pressure, and can we classify elevated risk across patient demographics?
• Data Science Question: How can I work with clinical patient records to evaluate elevated resting blood pressure and establish structured risk profiles using R?

Strategy & Technical Approach

1. Data Import: The raw CSV data will be imported directly into R from the URL cited in the introduction section.
2. Data Cleaning & Wrangling:
   • Check data types
   • Look for missing values
   • Clean column headers
   • Recode variables as needed
   • Select a subset of data needed for analysis
3. Exploratory Visualizations: Use ggplot2 to visualize relationships and identify patient risks.

Anticipated Data Challenges

• Missing Data Handling: The dataset may contain missing values records that may require filtering.
• Data Types: May need to create factors to organize categorical variables.
• Outliers: Check for extreme values in variables.