This analysis explores historical stock price trends using key technical indicators to assess market behavior. It includes: Daily Returns & Volatility: Understanding stock price fluctuations. Moving Averages (50-day & 200-day): Identifying market trends. Bollinger Bands: Detecting overbought and oversold conditions. Correlation Heatmap: Analyzing relationships between stock metrics. Key Insights: ✔ Moving averages help confirm trend direction. ✔ Bollinger Bands indicate potential price reversals. ✔ Correlation analysis aids in portfolio diversification. This structured approach provides valuable insights for traders and investors to enhance decision-making.

This report analyzes Cyclistic’s bike-share data for Q1 2020, comparing ride patterns between annual members and casual riders. Using RStudio, ggplot2, and tidyverse, key insights on ride duration, frequency, and weekday trends are visualized. Recommendations are provided to help convert casual riders into members.