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A smoothing technique that averages consecutive observations within a sliding window to reduce noise and reveal trends.
DESCRIPTION
A moving average replaces each point with the average of neighboring observations within a fixed window. It reduces short-term fluctuations, making trends and cycles easier to see. Variants include simple, weighted, and exponential moving averages. Window size trades noise reduction against lag and responsiveness. Moving averages are foundational for exploratory analysis, forecasting pre-processing, and technical indicators.
ALTERNATIVE DEFINITIONS
Investopedia
The reason for calculating the moving average is to help smooth out price data by creating a constantly updated average price.
Focuses on smoothing and continually updated average.
Forecasting: Principles and Practice
A moving average smooths a time series by averaging consecutive observations in a rolling window.
General time-series-specific description of smoothing.
NIST/SEMATECH
Moving averages are used to smooth data by replacing each data point with the average of neighboring points.
Emphasizes smoothing by neighborhood averaging in quality control context.
RELATED TERMS
Simple Moving Average Time Series Smoothing Trend Noise Reduction Window Size Filter ARIMA Rolling Mean Seasonality
COMPETING TERMS
RELATIONS
KNOWLEDGE AREAS
Data Science Mathematics Data Visualization
TARGET AUDIENCE
Data Analyst Data Scientist BI Specialist
EXTERNAL SOURCES
- Wikipedia - Moving average
- Hyndman & Athanasopoulos - Detailed treatment of moving averages
- NIST/SEMATECH - Quality control perspective on smoothing
TOP QUESTIONS
What is a Moving Average in time series?
It is a rolling mean that smooths short-term noise. It helps reveal underlying trend and seasonality.
Category: Definition
How do I choose the window size for a Moving Average?
Larger windows smooth more but add lag; smaller windows respond faster. Choose based on noise level and seasonality.
Category: HowTo
What is the difference between SMA and EMA?
SMA equally weights observations; EMA weights recent observations more, improving responsiveness.
Category: Comparison
Can Moving Averages distort seasonal patterns?
Yes, poor window choices can blur seasonality. Seasonal moving averages can mitigate distortion.
Category: Mistakes
Are Moving Averages useful before ARIMA?
They can help visualize structure but are usually not applied directly before ARIMA modeling.
Category: Practice
What is a centered Moving Average?
It assigns the average to the center of the window, reducing phase shift compared to trailing windows.
Category: Concepts
Do Moving Averages handle missing data?
Most implementations require complete windows; imputation or variable window sizes may be used.
Category: Operations
Where are Moving Averages used beyond time series?
In signal processing, control charts, and feature engineering for smoothing and trend extraction.
Category: Application
What is a common pitfall with Moving Averages?
Interpreting smoothed lines as forecasts without considering lag and uncertainty.
Category: Mistakes