Consider the following to answer the question(s) below:
Monthly closing stock prices for a utility company were obtained from January 2014 through August 2015. A regression model was estimated to describe the trend in closing stock prices over time.
-Which of the following statement is true about autocorrelation?
A) We use autocorrelation to predict values of y for values x far from the ones used to find the linear model equation.
B) When a regression model applied to autocorrelated data, the Independence assumption is satisfied.
C) When data highly correlated over time, each data point is similar to those around it. The Independence assumption is violated.
D) We use χ2 statistic to test for autocorrelation.
E) Autocorrelation occurs only if there is at least one extreme outlier.

Question

Consider the following to answer the question(s) below:
Monthly closing stock prices for a utility company were obtained from January 2014 through August 2015. A regression model was estimated to describe the trend in closing stock prices over time. 
-Which of the following statement is true about autocorrelation?
A) We use autocorrelation to predict values of y for values x far from the ones used to find the linear model equation. 
B) When a regression model applied to autocorrelated data, the Independence assumption is satisfied. 
C) When data highly correlated over time, each data point is similar to those around it. The Independence assumption is violated. 
D) We use χ2 statistic to test for autocorrelation. 
E) Autocorrelation occurs only if there is at least one extreme outlier.

Quizplus · Accepted Answer

Autocorrelation refers to the correlation among successive values of the error term in a time series data. When data is highly correlated over time, each data point is similar to those around it, and the Independence assumption in regression is violated. Autocorrelation can be tested using statistical tests such as the Durbin-Watson test, not the χ2 statistic. Autocorrelation does not require the presence of extreme outliers. Option A is incorrect because auto correlation measures the dependence between observations at different time lags and not used to predict the value of Y for values of X far from the ones used to find the linear model equation. Option B is incorrect because when data is autocorrelated, the Independence assumption is violated. Option E is incorrect because the presence of extreme outlier does not necessarily indicate the existence of autocorrelation.

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