📚 What is a Time Series?
A time series is a sequence of data points recorded at regular intervals over time. It's widely used in fields like finance, weather forecasting, and stock market analysis.
🔍 Key Characteristics
- Ordered Data: Values are indexed by time (e.g., minutes, hours, days).
- Trend: Long-term progression (upward, downward, or stable).
- Seasonality: Regular patterns within fixed time periods (e.g., daily, monthly).
- Noise: Random fluctuations unrelated to the underlying pattern.
🌐 Common Applications
- Finance: Stock price prediction 📈
- Meteorology: Weather pattern analysis ☁️
- Retail: Sales forecasting 🛍️
- Healthcare: Patient vital sign monitoring ❤️
🧠 Essential Concepts to Master
- Stationarity: A time series with constant mean and variance over time.
- Lag: The time difference between consecutive data points.
- Smoothing Techniques: Moving average 📊 or exponential smoothing 📈
- Decomposition: Breaking down data into trend, seasonality, and residual components.
📖 Next Steps for Learning
Ready to dive deeper? Explore our Time Series Analysis Tutorial for advanced techniques!