3 Types of Seasonality and How to Detect Them

<p>Analyzing and dealing with seasonality is a key exercise in time series analysis.</p> <p>In this article, we&rsquo;ll describe three types of seasonality and how to detect them.</p> <h1>What is seasonality?</h1> <p>Seasonality is one of the key components that make up a time series. Seasonality refers to systematic movements that repeat over a given period with a similar intensity.</p> <p>Seasonal variations can be caused by various factors, such as weather, calendar, or economic conditions. Examples abound in various applications. Flights are more expensive in the summer because of vacations and tourism. Another example is consumer spending which increases in December due to holidays.</p> <p>Seasonality means the average value in some periods will be different than the average value at other times. This issue&nbsp;<a href="https://medium.com/towards-data-science/understanding-time-series-trend-addfd9d7764e" rel="noopener">causes the series to be non-stationary</a>. This is why it is important to analyze seasonality when building a model.</p> <p><a href="https://towardsdatascience.com/3-types-of-seasonality-and-how-to-detect-them-4e03f548d167"><strong>Click Here</strong></a></p>