What are time series and how are they analyzed?

What are time series and how are they analyzed?

Time series are sequences of data points collected or recorded at specific time intervals. They are analyzed to identify trends, seasonal patterns, and other temporal structures.

Can you explain the difference between stationary and non-stationary time series?

A stationary time series has constant mean and variance over time, while a non-stationary series shows trends or seasonal effects.

What methods are commonly used for time series forecasting?

Common methods include ARIMA, Exponential Smoothing, and Seasonal Decomposition of Time Series (STL). Each has its own strengths depending on the data.

How do I check if a time series is stationary?

You can use statistical tests like the Augmented Dickey-Fuller test or visualize the series with plots to check for stationarity.

What are some applications of time series analysis?

Time series analysis is used in various fields such as finance for stock price prediction, economics for GDP forecasting, and environmental science for climate data analysis.