Stationarity Meaning: Definition, Examples, and Translations
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stationarity
[ˌsteɪʃəˈnerɪti ]
Definition
Context #1 | Noun
time series analysis
Stationarity is a property of a time series where the statistical properties such as mean, variance, and autocorrelation are constant over time.
Examples of usage
- The stationarity of a time series is important for accurate forecasting.
- Detecting non-stationarity in a time series can help in identifying trends or seasonal patterns.
Translations
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Interesting Facts
Mathematics & Statistics
- In time series analysis, a stationary process shows statistical properties that do not change over time, like mean and variance.
- Stationarity is crucial for many statistical models; if data isn't stationary, it might not yield reliable results.
- There are several types of stationarity, including strict and weak, each having different requirements for stability over time.
Economics
- In economics, many theories assume stationarity for modeling, implying that economic indicators will behave consistently over time.
- Stationary assumptions impact forecasts; if an economy is not stationary, predictions can be wildly inaccurate.
- The concept challenges economists to identify trends that may imply non-stationarity, helping them refine their analyses.
Physics
- In physics, the concept of stationarity applies to systems in equilibrium, where forces and energies remain constant.
- Equilibrium states in thermodynamics, where properties do not change over time, illustrate a form of stationarity.
- Non-stationary processes are of great interest, such as those that undergo phase transitions, reflecting a shift in stability.
Psychology
- Stationarity in behavioral patterns suggests that certain habits or traits can remain unchanged over extended periods.
- Psychological studies often analyze whether behaviors show stability or change, guiding understanding of human development.
- Longitudinal studies frequently assume stationarity, as they track the same individuals over time to observe consistency in responses.
Origin of 'stationarity'
Main points about word origin
- The term derives from the Latin 'stationarius', meaning 'standing still', which reflects its core idea of stability.
- It first appeared in literature around the 19th century, particularly in mathematical texts discussing time series.
- The prefix 'sta-' used in the word comes from roots meaning 'to stand', highlighting its conceptual link to stability.
The concept of stationarity in time series analysis dates back to the early 20th century when statisticians started exploring the behavior of data over time. It plays a crucial role in forecasting and modeling various phenomena, from stock prices to weather patterns.