Hair-Eye Color Breakdown

Test

I attempted to predict the popularity of upcoming movie releases.

This R script performs a comprehensive statistical and machine learning analysis of a health and fitness dataset. The Health and Fitness dataset can be accessed in the following link: Kaggle. It begins with descriptive statistics of key variables, then explores relationships between features. Specifically, it runs a regression model predicting Calories_Burned based on BMI, Workout_Frequency, and Workout_Type. The code also calculates correlations, including the relationship between Water_Intake and Avg_BPM, and between Workout_Type and Calories_Burned, to assess how hydration and exercise style influence performance. To uncover patterns in member behavior, it applies K-means clustering on variables such as Age, Avg_BPM, and Calories_Burned, grouping individuals into distinct activity level categories. Additionally, the script visualizes the distributions of calories and exercise types, highlighting measures of central tendency along with the 25th and 75th percentiles. Together, this analysis provides insights into how workout habits, body metrics, and exercise choices shape overall fitness outcomes.

《因果效应：研究设计和因果关系导论》

Providing access on public domain for retrieving the files a) HTML b) RMD c) CSV files