Pymaceuticals, Inc. specializes in developing anti-cancer medications. They conducted an animal study to test treatments for squamous cell carcinoma (SCC), a common type of skin cancer. The study involved 249 mice with SCC tumors who received different drug regimens over 45 days. The main aim was to evaluate how well Capomulin, one of Pymaceuticals' drugs, worked compared to others.
As a senior data analyst at Pymaceuticals, your job is to analyze the study data and create clear summaries and visuals for the company's technical report.
- Prepare the Data
- Combine mouse metadata and study results into one dataset.
- Identify unique mouse IDs and remove any duplicates.
- Generate Summary Statistics
- Calculate mean, median, variance, standard deviation, and SEM of tumor volume for each drug regimen.
- Create Bar Charts and Pie Charts
- Show the number of mice for each drug regimen using bar charts.
- Display the gender distribution of mice using pie charts.
- Calculate Quartiles, Find Outliers, and Create a Box Plot
- Determine quartiles, IQR, and potential outliers for final tumor volume in promising treatments.
- Create a box plot to visualize the tumor volume distribution.
- Calculate Correlation and Regression
- Find the correlation between mouse weight and tumor volume for Capomulin.
- Develop a linear regression model to understand their relationship.
By analyzing and visualizing the study data, Pymaceuticals can gain insights into how their treatments perform. T his will help them make informed decisions about future drug development.