This repository contains the statistical analysis of a dataset that explores various health-related factors and their impact on individuals well-being. The analysis was conducted using Python 3.11 with libraries such as pandas, matplotlib, and scipy.
The report.ipynb notebook presents a statistical analysis of a dataset containing information about individuals' health-related factors. The dataset includes variables such as gender, age, occupation, sleep duration, quality of sleep, physical activity level, stress level, BMI category...
The analysis aims to explore relationships, patterns, and trends within the data to gain insights into factors that may impact individuals' health and well-being.
Key findings from the analysis include:
- Sleep Duration: The mean sleep duration is approximately 7.13 hours, ranging from 5.8 to 8.5 hours.
- Age: The mean age is approximately 42.18 years, ranging from 27 to 59 years.
- Heart Rate: The mean resting heart rate is around 70.17 beats per minute (bpm), ranging from 65 to 86 bpm.
- Daily Steps: The average number of steps taken per day is 6816.84, ranging from 3000 to 10,000 steps.
Hypothesis testing revealed:
- Difference in Sleep Duration Between Genders: There is a significant difference in sleep duration between genders (p-value < 0.05).
- Relationship Between Physical Activity Level and Sleep Quality: There is a significant positive correlation between physical activity level and sleep quality (p-value < 0.05).
These findings provide valuable insights into factors that influence sleep patterns and overall well-being.
For more details, please refer to the report.ipynb notebook or report.html html file.