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    Question

    Which test is commonly applied in time series analysis

    to determine whether a series is stationary?
    A Shapiro-Wilk Test Correct Answer Incorrect Answer
    B Dickey-Fuller Test Correct Answer Incorrect Answer
    C Chi-Square Test Correct Answer Incorrect Answer
    D Jarque-Bera Test Correct Answer Incorrect Answer
    E ANOVA Correct Answer Incorrect Answer

    Solution

    The Dickey-Fuller Test is a widely used statistical test in time series analysis to evaluate if a series is stationary. It tests the null hypothesis that a unit root is present in the series, indicating non-stationarity. If the test statistic is significantly lower than a threshold (indicating a low p-value), the null hypothesis is rejected, suggesting the data is stationary. Achieving stationarity is crucial for time series models like ARIMA, which assume stable mean and variance over time. Therefore, the Dickey-Fuller Test is essential for determining whether data requires differencing or other transformations before analysis. The other options are incorrect because: • Option 1 (Shapiro-Wilk Test) checks for normality, not stationarity. • Option 3 (Chi-Square Test) evaluates relationships between categorical variables. • Option 4 (Jarque-Bera Test) tests normality in large samples, not stationarity. • Option 5 (ANOVA) assesses mean differences across groups, unrelated to stationarity.

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