Exploratory Data Analysis of FitBit Data

Objective

The primary objective of this analysis is to conduct a comprehensive exploratory study on FitBit data. We aim to uncover patterns and derive insights regarding the health and fitness activities of users. This involves examining metrics such as daily steps, sleep patterns, and calorie expenditure.

Goals

• Enhance Understanding: Utilize the insights gathered from the data to better understand health and wellness trends among FitBit users.
• Correlation Analysis: Investigate how various health metrics like daily steps, sleep quality, and calorie burn interrelate, providing a holistic view of user behaviors and health.

Insights Sought

• Daily Steps: Analyze step count data to observe user activity levels and identify active vs sedentary trends.

• Sleep Patterns: Explore patterns in sleep quality and duration to assess their impact on overall health.

• Calorie Expenditure: Evaluate the relationship between calorie burn and physical activities to gauge the efficiency and effectiveness of different types of exercise.

Analysis Approach

The analysis will involve:

• Cleaning and preprocessing the data to ensure accuracy and usability.
• Using statistical tools and visualization techniques to identify trends and patterns.
• Conducting correlation studies between different health metrics.