Public Health Survey Descriptive Analysis

I have a raw dataset from a recent public-health survey that now needs a clear, publication-ready descriptive analysis. The file will arrive as a de-identified CSV with the full data dictionary; variables include standard demographic items plus several multi-item scales on health behaviors and service use.

Your task is to run thorough descriptive statistics—frequencies, proportions, means, medians, and appropriate measures of dispersion—highlighting any notable patterns or unexpected values. Visual summaries (bar charts, histograms, boxplots) are encouraged to make the findings accessible for non-technical readers. I prefer to work in R or Python (tidyverse, pandas, seaborn, ggplot2), but Stata or SPSS are equally acceptable if that is where you work fastest.

Deliverables
• A concise report (Word or PDF) describing the methodology and key findings
• An editable script or notebook with reproducible code
• Clean output tables and graphics ready for insertion into a manuscript or slide deck

I will review the code for reproducibility and expect the numbers in the report to match the script output exactly. If you spot data quality issues while exploring the file, flag them so we can decide on cleaning steps together.

Turnaround within one week is ideal, but let me know if you need a little more time.