Time Series Analysis
(การวิเคราะห์อนุกรมเวลา)
Definition
Time Series Analysis (การวิเคราะห์อนุกรมเวลา) Hard Skill
Time Series Analysis involves examining time-ordered data points to identify meaningful patterns, trends, and seasonal variations, enabling forecasting and informed decision-making.
Expertise Level
Level 1
Basic
1. Understands fundamental concepts of time series data and its components.
2. Can plot and visualize simple time series datasets.
3. Recognizes basic patterns like trends and seasonality in data.
Level 2
Intermediate
1. Applies statistical models such as moving averages and exponential smoothing.
2. Performs decomposition of time series to analyze trend, seasonal, and residual components.
3. Uses autocorrelation and partial autocorrelation functions for model identification.
Level 3
Advanced
1. Develops and implements advanced forecasting models like ARIMA, SARIMA, and GARCH.
2. Can handle multivariate time series and apply machine learning methods for prediction.
3. Evaluates model accuracy and optimizes models for complex real-world datasets.
