61. In time series analysis, what is the primary goal of "seasonal decomposition of time series" (STL)? A. To identify seasonality in the data B. To test for autocorrelation in residuals C. To remove outliers from the data D. To assess the model's goodness of fit Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
62. Which time series forecasting method is based on the assumption that future values of a series depend linearly on past values and past forecast errors? A. Moving Average B. Exponential Smoothing C. ARIMA D. Autoregressive Integrated Moving Average (ARIMA) Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option C No explanation is given for this question Let's Discuss on Board
63. What is the primary purpose of "forecasting horizon" in time series forecasting? A. To identify seasonality in the data B. To specify the length of a time series forecast C. To remove outliers from the data D. To evaluate the accuracy of forecasts Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
64. In time series analysis, what does the term "multicollinearity" refer to? A. High seasonality and trend B. High correlation between predictor variables C. High autocorrelation in residuals D. Correlation between independent variables Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
65. Which time series forecasting method involves combining several models' forecasts to improve prediction accuracy? A. Residual Analysis B. Ensemble Forecasting C. Exponential Smoothing D. ARIMA Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
66. In time series analysis, what is the primary goal of "bootstrap resampling"? A. To identify seasonality in the data B. To test for autocorrelation in residuals C. To remove outliers from the data D. To estimate the distribution of statistics Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
67. Which statistical method is commonly used to identify and remove trends and seasonality from time series data? A. Moving Average B. Exponential Smoothing C. Seasonal Decomposition of Time Series D. Detrending Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option D No explanation is given for this question Let's Discuss on Board
68. What is the primary objective of "heteroscedasticity testing" in time series analysis? A. To identify seasonality in the data B. To test for changing variance in residuals C. To remove outliers from the data D. To test for autocorrelation in residuals Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
69. In time series analysis, what is the purpose of "rolling forecasting origin"? A. To identify seasonality in the data B. To evaluate the accuracy of forecasts C. To remove outliers from the data D. To test for autocorrelation in residuals Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option B No explanation is given for this question Let's Discuss on Board
70. Which method in time series analysis is used to forecast future values by taking into account both trend and seasonality? A. Exponential Smoothing B. Moving Average C. ARIMA D. Seasonal Decomposition of Time Series Answer & Solution Discuss in Board Save for Later Answer & Solution Answer: Option A No explanation is given for this question Let's Discuss on Board
