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|Introduction to time series data
|Understanding the basics of time series data, including its characteristics and properties.
|Exploratory data analysis
|Analyzing and visualizing time series data to identify patterns, trends, and anomalies.
|Detrending and filtering
|Removing trends and applying filters to time series data to isolate the underlying patterns.
|Modeling time series
|Building statistical models to capture the underlying structure and behavior of time series data.
|Predicting future values or trends of a time series based on historical data and model analysis.
|Applications of time series
|Exploring real-world applications of time series analysis, such as demand forecasting and sales predictions.
|Nonlinear time series analysis
|Examining time series data that exhibit nonlinear behavior and applying specialized analysis techniques.
|Multivariate time series analysis
|Analyzing time series data with multiple variables or factors influencing the observations.
|Studying the behavior of complex and chaotic time series using mathematical models and algorithms.
|Financial time series analysis
|Applying time series analysis techniques to financial data for forecasting and risk assessment.