Overview
Time series analysis is a powerful statistical tool used to analyze data points collected over time. It helps in identifying trends, seasonal patterns, and other characteristics that can inform decision-making in various fields such as finance, economics, and environmental science. By understanding ...
Key Terms
Example: An upward trend in stock prices over several years.
Example: Increased ice cream sales during summer months.
Example: High autocorrelation in monthly sales data.
Example: A time series with constant mean and variance.
Example: Using ARIMA to predict future sales based on past data.
Example: Using exponential smoothing for short-term sales forecasts.
Related Topics
Statistical Modeling
The process of creating models to represent complex data relationships.
intermediateData Visualization
Techniques for representing data graphically to identify patterns.
beginnerMachine Learning for Time Series
Applying machine learning techniques to improve time series forecasting.
advancedKey Concepts
Trend AnalysisSeasonalityAutocorrelationForecasting