ayushverma135/sas-health-metrics-analysis-bmi-categorization-and-gender-insights

Using SAS, this project processes Excel data on individual statistics and health metrics. It calculates BMI, categorizes health status, and visualizes distributions through pie charts.

SAS-Health-Metrics-Analysis-BMI-Categorization-and-Gender-Insights

SAS Programming Introduction

SAS (Statistical Analysis System) programming is a versatile tool used for data management, statistical analysis, and reporting. It provides a comprehensive suite of functionalities for processing and analyzing data, including data import/export, data manipulation, statistical analysis, and visualization. SAS programming language is easy to learn and offers a wide range of procedures and functions to perform various analytical tasks.

It is widely used in industries such as finance, healthcare, marketing, and research for its robustness, scalability, and reliability in handling large datasets and producing accurate results. SAS programming can be executed in interactive mode through SAS Studio or batch mode using SAS programs, offering flexibility in workflow and analysis methods.

In this project, SAS is utilized to analyze individual statistics and health metrics, showcasing its versatility in data processing and visualization.

Overview

This SAS Health Metrics Analysis BMI Categorization and Gender Insights project aims to analyze individual statistics and health metrics using SAS programming. The project involves importing data from Excel sheets, calculating Body Mass Index (BMI), categorizing individuals based on BMI values, and visualizing the distribution of health status categories through pie charts.

Additionally, the project utilizes macros to generate frequency tables and reports, exploring relationships between gender and BMI status for comprehensive analysis.

Project Structure

• Data: Contains Excel sheets with individual statistics and health metrics in Input_Datasets dataset.
• Code: SAS Solution 1.sas code files for data importing, BMI calculation, categorization, visualization, and frequency table generation.
• Outputs: Results_ Solution 1.sas.pdf Output file including pie charts, frequency tables, and reports.
• README.md: Project overview, structure, and instructions.

Project Workflow

Sure, here are the steps broken down:

1. Import Data: Import data from Excel sheets containing statistics, history, and student health information.

2. Organize Data: Organize imported data to prepare for further analysis.

3. Convert Measurements: Convert weight and height measurements from the imported data into the metric system.

4. Calculate BMI: Utilize the metric weight and height measurements to calculate the Body Mass Index (BMI) for each individual.

5. Categorize Individuals: Categorize individuals based on their calculated BMI values into distinct health status groups.

6. Generate Pie Chart: Create a pie chart visualization to illustrate the distribution of health status categories among individuals.

7. Create Frequency Tables and Reports: Utilize macros to create frequency tables and reports, exploring relationships between gender and BMI status.

8. Analyze Relationships: Conduct an in-depth analysis of the relationships between gender and BMI status, as well as vice versa, using the generated frequency tables and reports.

9. Gain Insights: Extract valuable insights into the health profiles of the studied population, aiding informed decision-making processes.

Instructions

1. Data Preparation: Ensure Excel sheets with individual statistics and health metrics are available in the designated folder.

2. SAS Environment Setup: Configure SAS environment and ensure necessary libraries are accessible.

3. Code Execution: Execute the provided SAS code files in the specified order to import data, calculate BMI, categorize health status, visualize distributions, and generate frequency tables.

4. Review Outputs: Check the generated outputs in the "Outputs" folder including pie charts, frequency tables, and reports.

5. Exploratory Analysis: Explore the relationships between gender and BMI status using the generated frequency tables and reports.

Dependencies

• SAS software environment
• Excel files containing individual statistics and health metrics

Support the Project

If you find this project helpful and would like to support my work, consider sponsoring my GitHub profile. Your sponsorship helps maintain and improve projects like these.

And if you are interested in receiving a video solution for this project or have any further inquiries, please feel free to contact me via email at [email protected]. I'll be happy to assist you further.