The KPSS test assumes in the null hypothesis that a series is stationary. Choose one answer: Truth Falsehood
Answer (1)
The KPSS test, short for Kwiatkowski–Phillips–Schmidt–Shin test, is a statistical test used to check for stationarity in a time series. The null hypothesis (H0) in the KPSS test is that the series is stationary around a deterministic trend, which essentially means that any variations or fluctuations in the time series data are consistent and do not vary widely over time.
Here's a step-by-step explanation:
What is a Time Series? A time series is a sequence of data points collected or recorded at regular time intervals. Examples include daily stock prices or monthly sales data.
What does Stationarity mean? A time series is stationary if its statistical properties (like mean, variance) do not change over time. Stationarity is important in time series analysis, especially for forecasting.
KPSS Test Hypotheses:
Null Hypothesis (H0): The time series is stationary (no unit root).
Alternative Hypothesis (H1): The time series is not stationary (has a unit root).
Testing Purpose: The KPSS test helps to identify whether a series needs to be differenced to achieve stationarity, which is often a prerequisite for certain forecasting models, like ARIMA.
Conclusion: Because the null hypothesis of the KPSS test asserts that the series is stationary, the correct option is: Truth
Understanding stationarity and applying tests like KPSS helps analyze time series data effectively, leading to better forecasting and insights.
