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a).Time Series
It is not a specific model but a whole class of forecasting model based on historical data. It is a set of observed values, usually sales measures over successive period of time. Time series is based on a sequence of evenly spaced data points (weekly, monthly, and quarterly).
Semiannually or even annually e.g thoroughly sale of stock, daily sale of newspapers e.t.c.
forecasting time series data implies that future values are predicted only from past values but other variables no matter how potentially variable are ignored .
A time series typically has four components namely:
1. Trend- It is the gradual upward or downward movement of data overtime.
2. Cycles
3. Random variation
4. Trend components
.
b).Seasonality
It is the pattern that repeats itself after a period of days, e.g weeks, months, quarters etc.
C). Cycles
These are patterns in data that occur every several years. They are usually tied into the business cycles and are of importance in short term business analysis and planning. It may take several years before repeating itself.
NatalieR answered the question on June 10, 2022 at 13:38
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