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seasonality
In statistics, time series data is data collected at regular intervals. When there are patterns that repeat over known, fixed periods of time〔https://www.otexts.org/fpp/6/1〕 within the data set it is considered to be seasonality, seasonal variation, periodic variation, or periodic fluctuations. This variation can be either regular or semi-regular.
Seasonality may be caused by various factors, such as weather, vacation, and holidays〔|title=Influencing Factors|〕 and usually consists of periodic, repetitive, and generally regular and predictable patterns in the levels of a time series. Seasonality can repeat on a weekly, monthly or quarterly basis, these periods of time are structured and occur in a length of time less than a year. Seasonal fluctuations in a time series can be contrasted with cyclical patterns. The latter occur in a period of time that extends beyond a single year, these fluctuations are usually of at least two year〔https://www.otexts.org/fpp/6/1〕 and do not repeat over fixed periods of time.
Organizations facing seasonal variations, such as ice-cream vendors, are often interested in knowing their performance relative to the normal seasonal variation. Seasonal variations in the labor market can be attributed to the entrance of school leavers into the job market; as they aim to contribute to the workforce during their vacations, or upon the completion of their schooling. These regular changes are of less interest to those who study employment data than the variations that occur due to the underlying state of the economy. Where their focus is on how unemployment in the workforce has changed, despite the impact of the regular seasonal variations.〔https://www.otexts.org/fpp/6/1〕
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
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