In time series analysis, what is the purpose of "smoothing" methods such as exponential smoothing?
A. To add noise to the data
B. To identify seasonality in the data
C. To remove random fluctuations
D. To identify trends in the data
Which of the following is NOT a common method for measuring the similarity between time series data?
A. Euclidean distance
B. Pearson correlation coefficient (PCC)
C. Dynamic Time Warping (DTW)
D. Chi-squared distance
What is the primary goal of "lag plots" in time series analysis?
A. To identify outliers in the data
B. To visualize autocorrelation in the data
C. To identify seasonality in the data
D. To add noise to the data
In time series analysis, what does the "autocorrelation function" (ACF) measure?
A. Seasonal patterns
B. Trend patterns
C. Correlation between lagged values
D. Random noise
Which type of time series data is characterized by data points that are dependent on previous observations?
A. White noise
B. Stationary data
C. Autoregressive data
D. Independent data
What is the primary characteristic of a time series data set?
A. Random data
B. Data points are not related
C. Data is collected at irregular intervals
D. Data is collected over time
In time series analysis, what is the term for the repeating patterns that occur at regular intervals?
A. Outliers
B. Trends
C. Seasonality
D. Noise
Which type of time series data is characterized by a consistent upward or downward movement over time?
A. Stationary
B. Seasonal
C. Trend
D. White noise
What is the primary goal of "detrending" in time series analysis?
A. To remove seasonality from the data
B. To remove outliers from the data
C. To identify trends in the data
D. To add noise to the data
Which statistical method is commonly used to decompose a time series into its trend, seasonal, and residual components?
A. Fourier transformation
B. Principal Component Analysis (PCA)
C. Moving Average
D. Seasonal Decomposition of Time Series
