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Trends in time series data show long-term changes or patterns over time, such as increasing or decreasing values. Examples include population growth, stock market trends, or climate change. Seasonality refers to recurring patterns that follow a specific time frame, like daily, weekly, or yearly cycles. Examples comprise retail sales peaking during holidays, temperature fluctuations across seasons, or website traffic spiking during certain times of the day. These patterns can impact decision-making and forecasting, encouraging the employment of tools like seasonal decomposition or time series models to analyse and account for them in analysis.

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