Excel Statistical Study of Patient Records
Budget: ₹600 – ₹1,500 INR
I will provide a de-identified spreadsheet of patient records and need a skilled analyst to explore the data directly in Excel. The goal is to extract clear, trustworthy insights through two layers of statistical work:
• Descriptive statistics – means, medians, standard deviations, frequency counts, and any other summary measures that illuminate overall patterns in the cohort.
• Regression analysis – build and document models that explain how key variables (for example, age, treatment duration, or baseline scores) relate to outcomes. I’m happy to discuss which predictors make clinical sense once you have scanned the file.
Please clean and structure the data first so the formulas and Analysis ToolPak outputs run smoothly, then add concise interpretations next to each table or chart so a non-statistician can follow the story.
Deliverables for acceptance:
1. The Excel workbook with all cleaning steps, formulas, and regression outputs intact and editable.
2. An “Insights” tab summarising the main descriptive findings and the practical meaning of each regression coefficient.
3. Any supporting visualisations that clarify trends or model fit.
If you are comfortable navigating medical datasets and can keep patient information secure, let’s get started right away.
• Descriptive statistics – means, medians, standard deviations, frequency counts, and any other summary measures that illuminate overall patterns in the cohort.
• Regression analysis – build and document models that explain how key variables (for example, age, treatment duration, or baseline scores) relate to outcomes. I’m happy to discuss which predictors make clinical sense once you have scanned the file.
Please clean and structure the data first so the formulas and Analysis ToolPak outputs run smoothly, then add concise interpretations next to each table or chart so a non-statistician can follow the story.
Deliverables for acceptance:
1. The Excel workbook with all cleaning steps, formulas, and regression outputs intact and editable.
2. An “Insights” tab summarising the main descriptive findings and the practical meaning of each regression coefficient.
3. Any supporting visualisations that clarify trends or model fit.
If you are comfortable navigating medical datasets and can keep patient information secure, let’s get started right away.