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A time series is a set of observations recorded over time (daily, monthly, yearly). Businesses use time series to study sales trends, seasonal patterns, demand cycles and plan inventory, staffing and budgets. Time series analysis breaks data into components like trend and seasonality. This topic focuses on components of time series, the trend component, and the moving averages method used to measure trend.
A time series is data collected in chronological order at equal intervals of time (e.g., monthly sales for 12 months).
Often written as: (additive model) or (multiplicative model) at concept level.
Trend is the long-term general direction of the series (upward, downward or constant).
Seasonal variations are regular short-term patterns that repeat every year due to seasons, festivals or business cycles within a year.
Cyclical variations are wave-like movements around the trend lasting more than a year, caused by business cycles (expansion, recession).
Irregular variations are unpredictable changes caused by unexpected events (wars, floods, strikes).
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A time series is a set of observations recorded over time (daily, monthly, yearly). Businesses use time series to study sales trends, seasonal patterns, demand cycles and plan inventory, staffing and budgets. Time series analysis breaks data into components like trend and seasonality. This topic focuses on components of time series, the trend component, and the moving averages method used to measure trend.
A time series is data collected in chronological order at equal intervals of time (e.g., monthly sales for 12 months).
Often written as: (additive model) or (multiplicative model) at concept level.
Trend is the long-term general direction of the series (upward, downward or constant).
Seasonal variations are regular short-term patterns that repeat every year due to seasons, festivals or business cycles within a year.
Cyclical variations are wave-like movements around the trend lasting more than a year, caused by business cycles (expansion, recession).
Irregular variations are unpredictable changes caused by unexpected events (wars, floods, strikes).
Moving averages smooth short-term fluctuations to show trend.
Steps:
If the moving average period is even (e.g., 4-quarter), averages lie between periods, so we compute a centered moving average by averaging two successive moving averages.
From this topic
Components of a time series include:
(Any three components including Irregular (I) can be written.)
Seasonal vs cyclical differences:
(Any three points can be written.)
A time series is a set of observations recorded over time at equal intervals, such as monthly sales, quarterly profits or yearly production. Time series analysis helps understand patterns and supports forecasting and planning.
A time series is commonly explained using four components:
At concept level, the series may be represented as Y = T + S + C + I (additive) or Y = T×S×C×I (multiplicative).
Thus, separating components helps managers understand why sales change and improves forecasting and decision making.