EMC Proven Professional – Data Science and Big Data Analytics — Question 24

You are analyzing a time series and want to determine its stationarity. You also want to determine the order of autoregressive models.
How are the autocorrelation functions used?

Answer options

• A. ACF as an indication of stationarity, and PACF for the correlation between Xt and Xt-k not explained by their mutual correlation with X1 through Xk-1.
• B. PACF as an indication of stationarity, and ACF for the correlation between Xt and Xt-k not explained by their mutual correlation with X1 through Xk-1.
• C. ACF as an indication of stationarity, and PACF to determine the correlation of X1 through Xk-1.
• D. PACF as an indication of stationarity, and ACF to determine the correlation of X1 through Xk-1.

Correct answer: A

Explanation

The correct answer is A because the Autocorrelation Function (ACF) helps determine stationarity, while the Partial Autocorrelation Function (PACF) identifies the correlation between Xt and Xt-k after accounting for the influence of other variables. Options B, C, and D incorrectly assign the roles of ACF and PACF, leading to a misunderstanding of their applications in time series analysis.