BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -Seasonal patterns are recognized by observing recurring patterns over successive periods. Seasonality is the number of time steps that it takes for a full data cycle, after which the cycle repeats throughout the time series.

Detailed explanation-2: -Seasonality is a characteristic of a time series in which the data experiences regular and predictable changes that recur every calendar year. Any predictable fluctuation or pattern that recurs or repeats over a one-year period is said to be seasonal.

Detailed explanation-3: -A seasonal pattern occurs when a time series is affected by seasonal factors such as the time of the year or the day of the week. Seasonality is always of a fixed and known frequency.

Detailed explanation-4: -There are typically four general types of patterns: horizontal, trend, seasonal, and cyclical.

Detailed explanation-5: -A level or horizontal pattern exists when data values fluctuate around a constant mean. This is the simplest pattern and the easiest to predict. An example is sales of a product that do not increase or decrease over time.