I will supply a de-identified Excel file containing patient records. Your task is to turn that raw sheet into a compact statistical workbook. First, clean or flag any missing or inconsistent entries so the dataset is ready for analysis. Then, on a clearly labelled “Descriptives” tab, calculate mean, median, mode, standard deviation and any other basic metrics that shed light on age, lab values, length-of-stay and similar variables. Next, run regression analyses that explore relationships I specify—e.g., length-of-stay versus age, or readmission risk versus multiple predictors. Use Excel’s built-in Data Analysis Toolpak or, if you prefer, embed results generated in R or Python so long as the final outputs live inside the workbook and update from the original data. Deliverables: • Cleaned dataset (same workbook) • Descriptive statistics sheet with clear headings and formulas visible • Regression output sheet(s) with coefficient tables, R² and p-values • Brief explanatory note summarising findings and pointing me to key cells/tabs The file should be self-contained: no external links or macros that trigger security warnings. Consistent formatting, readable labels and concise comments will help me audit and reuse your work quickly.